Filippo Sanfilippo, Timothy Wiley and Rebekah Rousi. RoboCup Soccer Autonomy Uprising: How Crowds, Referees, and Humanoid Robots Are Redefining the Future of Human-Robot Interaction. In Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction. 2025, 1131–1139. URL PDF BibTeX

@inproceedings{sanfilippo2025robocup,
	title = "RoboCup Soccer Autonomy Uprising: How Crowds, Referees, and Humanoid Robots Are Redefining the Future of Human-Robot Interaction",
	author = "Sanfilippo, Filippo and Wiley, Timothy and Rousi, Rebekah",
	abstract = "This paper explores the dynamics of Human-Robot Interaction (HRI) in public spaces, focusing on how humanoid robots engage with human crowds in the competitive RoboCup Soccer environment. We examine the role of spectatorship, where emotional engagement arises through indirect observation of engineering-driven competition, drawing parallels between human soccer and robot sports. The potential for autonomous systems to elicit collective emotions and systematically study such experiences is investigated. Using the Autonomy Levels for Unmanned Systems (ALFUS) framework, we assess RoboCup soccer robots' autonomy in terms of mission complexity (MC), environmental complexity (EC), and external system independence (ESI). Additionally, the Autonomy and Technology Readiness Assessment (ATRA) method supports gradual capability enhancement, providing a roadmap to higher autonomy. Based on this established methodology, we introduce the Robot-Crowd Interaction Framework (R-CIF), a novel conceptual framework defining the roles of actors involved, to connect theoretical insights with real-world applications. This work highlights the significance of crowd affectivity in robotic sports to boost public engagement and proposes directions for future research on collective emotional dynamics in HRI.",
	booktitle = "Proceedings of the 2025 ACM/IEEE International Conference on Human-Robot Interaction",
	pages = "1131--1139",
	year = 2025,
	pdf = "http://filipposanfilippo.inspitivity.com/publications/RoboCup-Soccer-Autonomy-Uprising-How-Crowds-Referees-and-Humanoid-Robots-Are-Redefining-the-Future-of-Human-Robot-Interaction.pdf",
	url = "https://dl.acm.org/doi/abs/10.5555/3721488.3721634"
}

Even Falkenberg LangÅs, Muhammad Hamza Zafar and Filippo Sanfilippo. Exploring the synergy of human-robot teaming, digital twins, and machine learning in industry 5.0: A step towards sustainable manufacturing. Journal of Intelligent Manufacturing, pages 1–24, 2025. PDF, DOI BibTeX

@article{langaas2025exploring,
	title = "Exploring the synergy of human-robot teaming, digital twins, and machine learning in industry 5.0: A step towards sustainable manufacturing",
	author = "Lang{\aa}s, Even Falkenberg and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	journal = "Journal of Intelligent Manufacturing",
	pages = "1--24",
	year = 2025,
	publisher = "Springer",
	doi = "https://doi.org/10.1007/s10845-025-02580-x",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/exploring-the-synergy-of-human-robot-teaming-digital-twins-and-machine-learning-in-Industry-5-a-step-towards-sustainable-manufacturing.pdf"
}

Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Federated Learning-Enhanced Edge Deep Learning Model for EMG-Based Gesture Recognition in Real-Time Human-Robot Interaction. IEEE Sensors Journal, 2025. PDF, DOI BibTeX

@article{zafar2025federated,
	title = "Federated Learning-Enhanced Edge Deep Learning Model for EMG-Based Gesture Recognition in Real-Time Human-Robot Interaction",
	author = "Zafar, Muhammad Hamza and Moosavi, Syed Kumayl Raza and Sanfilippo, Filippo",
	journal = "IEEE Sensors Journal",
	year = 2025,
	publisher = "IEEE",
	doi = "https://doi.org/10.1109/JSEN.2025.3529841",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/federated-learning-enhanced-edge-deep-learning-model-for-emg-based-gesture-recognition-in-real-time-human-robot-interaction.pdf"
}

Alf Stian Sundo Gonsholt, Eivind Enea Greca, Mustapha Haddad, Muhammad Hamza Zafar and Filippo Sanfilippo. Enhanced Human-Robot Teaming Through Attention Multi Convolutional Neural Network-Based Multi-Modal Sensor Fusion for Hand Gesture Recognition and Orientation Control. In Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS 2025), Big Island, Hawaii, United States of America. 2025, 590–599. URL BibTeX

@inproceedings{sanfilippo-2025-HRT,
	title = "Enhanced Human-Robot Teaming Through Attention Multi Convolutional Neural Network-Based Multi-Modal Sensor Fusion for Hand Gesture Recognition and Orientation Control",
	author = "Gonsholt, Alf Stian Sundo and Greca, Eivind Enea and Haddad, Mustapha and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS 2025), Big Island, Hawaii, United States of America",
	pages = "590--599",
	year = 2025,
	abstract = "Our study aims at enhancing Human-Robot Interaction, Collaboration, and Teaming (HRI/C/T) in industrial automation by developing a novel framework for real-time gesture control of a robotic hand. We use an Inertial Measurement Unit (IMU) sensor for precise orientation control of the end effector, and surface Electromyography (sEMG) sensors to detect muscle movements. The sEMG signals are processed by an Attention-based Multi Convolutional Neural Network (A-MCNN) for accurate gesture detection, enabling the robotic hand to mimic these gestures in real-time. Our method achieves notable results for gesture recognition, with the A-MCNN model attaining an accuracy of 97.89%, a precision of 97.49%, a recall of 97.71%, and an F1 score of 97.65%. This integration of IMU and sEMG technologies with advanced neural networks creates a responsive and intuitive control mechanism, improving safety, usability, and interaction of collaborative robots in shared workspaces. Our approach aims to transition towards Human-Robot Teaming (HRT), significantly advancing the seamless and safe integration of robots in industrial environments, enhancing productivity and collaboration.",
	url = "https://hdl.handle.net/10125/108907"
}

Filippo Sanfilippo, Muhammad Hamza Zafar, Timothy Wiley and Fabio Zambetta. From caged robots to high-fives in robotics: Exploring the paradigm shift from human–robot interaction to human–robot teaming in human–machine interfaces. Journal of Manufacturing Systems 78:1-25, 2025. URL PDF, DOI BibTeX

@article{SANFILIPPO20251,
	title = "From caged robots to high-fives in robotics: Exploring the paradigm shift from human–robot interaction to human–robot teaming in human–machine interfaces",
	journal = "Journal of Manufacturing Systems",
	volume = 78,
	pages = "1-25",
	year = 2025,
	issn = "0278-6125",
	doi = "https://doi.org/10.1016/j.jmsy.2024.10.015",
	url = "https://www.sciencedirect.com/science/article/pii/S0278612524002437",
	author = "Filippo Sanfilippo and Muhammad {Hamza Zafar} and Timothy Wiley and Fabio Zambetta",
	keywords = "Human–robot interaction, Human–robot collaboration, Human–robot teaming, Human–machine interfaces",
	abstract = "Multi-modal human–machine interfaces have recently undergone a remarkable transformation, progressing from simple human–robot interaction (HRI) to more advanced human–robot collaboration (HRC) and, ultimately, evolving into the concept of human–robot teaming (HRT). The aim of this work is to delineate a progressive path in this evolving transition. A structured, position-oriented review is proposed. Rather than aiming for an exhaustive survey, our objective is to propose a structured approach in a field that has seen diverse and sometimes divergent definitions of HRI/C/T in the literature. This conceptual review seeks to establish a unified and systematic framework for understanding these paradigms, offering clarity and coherence amidst their evolving complexities. We focus on integrating multiple sensory modalities — such as visual, aural, and tactile inputs — within human–machine interfaces. Central to our approach is a running use case of a warehouse workflow, which illustrates key aspects including modelling, control, communication, and technological integration. Additionally, we investigate recent advancements in machine learning and sensing technologies, emphasising robot perception, human intention recognition, and collaborative task engagement. Current challenges and future directions, including ethical considerations, user acceptance, and the need for explainable systems, are also addressed. By providing a structured pathway from HRI to HRT, this work aims to foster a deeper understanding and facilitate further advancements in human–machine interaction paradigms.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/from-caged-robots-to-high-fives-in-robotics-exploring-the-paradigm-shift-from-human-robot-interaction-to-human-robot-teaming-in-human-machine-interfaces.pdf"
}

Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor and Filippo Sanfilippo. An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease. Healthcare Analytics 7:100374, 2025. URL PDF, DOI BibTeX

@article{SALMANBUKHARI2025100374,
	title = "An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease",
	journal = "Healthcare Analytics",
	volume = 7,
	pages = 100374,
	year = 2025,
	issn = "2772-4425",
	doi = "https://doi.org/10.1016/j.health.2024.100374",
	url = "https://www.sciencedirect.com/science/article/pii/S2772442524000765",
	author = "Syed Muhammad {Salman Bukhari} and Muhammad Hamza Zafar and Syed Kumayl {Raza Moosavi} and Majad Mansoor and Filippo Sanfilippo",
	keywords = "Heart disease prediction, Convolutional neural network, Grasshopper optimization, Deep learning",
	abstract = "Cardiovascular disease is the leading cause of death worldwide, including critical conditions such as blood vessel blockage, heart failure, and stroke. Accurate and early prediction of heart disease remains a significant challenge due to the complexity of symptoms and the variability of contributing factors. This study proposes a novel hybrid model integrating a Stacked Convolutional Neural Network (SCNN) with the Levy Flight-based Grasshopper Optimization Algorithm (LFGOA) to address this challenge. The SCNN provides robust feature extraction, while LFGOA enhances the model by optimizing hyperparameters, improving classification accuracy, and reducing overfitting. The proposed approach is evaluated using four publicly available heart disease datasets, each representing diverse clinical and demographic features. Compared to traditional classifiers, including Regression Trees, Support Vector Machine, Logistic Regression, K-Nearest Neighbors, and standard Neural Networks, the SCNN-LFGOA consistently outperforms these methods. The results highlight that the SCNN-LFGOA achieves an average accuracy of 99%, with significant improvements in specificity, sensitivity, and F1-Score, showcasing its adaptability and robustness across datasets. This study highlights the SCNN-LFGOA's potential as a transformative tool for early and accurate heart disease prediction, contributing to improved patient outcomes and more efficient healthcare resource utilization. By combining deep learning with an advanced optimization technique, this research introduces a scalable and effective solution to a critical healthcare problem.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/an-integrated-stacked-convolutional-neural-network-and-the-levy-flight-based-grasshopper-optimization-algorithm-for-predicting-heart-disease.pdf"
}

Filippo Sanfilippo and Muhammad Hamza Zafar. Human-Robot Teaming: A Universal Controller with Multi-Modal Feedback for Emergency Response Robots. In Proc. of the 9th International Conference on Robotics and Automation Engineering (ICRAE 2024), Singapore, Singapore. 2024, . PDF BibTeX

@inproceedings{UniversalControllerSanfilippo2024,
	author = "Sanfilippo, Filippo and Zafar, Muhammad Hamza",
	booktitle = "Proc. of the 9th International Conference on Robotics and Automation Engineering (ICRAE 2024), Singapore, Singapore",
	title = "Human-Robot Teaming: A Universal Controller with Multi-Modal Feedback for Emergency Response Robots",
	year = 2024,
	pages = "",
	abstract = "This work presents the development of a universal wireless controller that supports the Robot Operating System (ROS), with a focus on enhancing system reliability and safety in Human-Robot Teaming (HRT). The controller is designed to provide multi-modal auditory, visual, and tactile feedback mechanisms, ensuring robust and reliable communication between human operators and various robots during collaborative emergency scenarios. The primary objective is to create an intuitive and unified interface that not only facilitates efficient collaboration but also significantly enhances the safety of operations by minimising the risk of human errors in dynamic and unpredictable environments. By integrating ROS capabilities with diverse sensorial feedback modalities, the controller improves situational awareness (SA) and operational reliability, enabling human operators, such as first responders, to maintain control and make informed decisions under pressure. A use case involving the navigation of a quadruped robot through an obstacle-filled environment is presented to demonstrate the controller's practical benefits in ensuring safety and reliability during complex tasks. The sequence of operations, including safe navigation, reliable victim proximity indication, and secure emergency stops, highlights the controller’s effectiveness in real-world scenarios, emphasising its role in promoting both system reliability and operational safety.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/human-robot-teaming-a-universal-controller-with-multi-modal-feedback-for-emergency-response-robots.pdf"
}

Ferial ElRobrini, Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Nedaa Al-Tawalbeh, Naureen Akhtar and Filippo Sanfilippo. Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review. Energy and AI 18:100438, 2024. URL PDF, DOI BibTeX

@article{ELROBRINI2024100438,
	title = "Federated learning and non-federated learning based power forecasting of photovoltaic/wind power energy systems: A systematic review",
	journal = "Energy and AI",
	volume = 18,
	pages = 100438,
	year = 2024,
	issn = "2666-5468",
	doi = "https://doi.org/10.1016/j.egyai.2024.100438",
	url = "https://www.sciencedirect.com/science/article/pii/S2666546824001046",
	author = "Ferial ElRobrini and Syed Muhammad Salman Bukhari and Muhammad Hamza Zafar and Nedaa Al-Tawalbeh and Naureen Akhtar and Filippo Sanfilippo",
	keywords = "Privacy-preserving, Federated learning, Transfer learning, PV power forecasting, Wind power forecasting, Deep learning",
	abstract = "Renewable energy sources, particularly photovoltaic and wind power, are essential in meeting global energy demands while minimising environmental impact. Accurate photovoltaic (PV) and wind power (WP) forecasting is crucial for effective grid management and sustainable energy integration. However, traditional forecasting methods encounter challenges such as data privacy, centralised processing, and data sharing, particularly with dispersed data sources. This review paper thoroughly examines the necessity of forecasting models, methodologies, and data integrity, with a keen eye on the evolving landscape of Federated Learning (FL) in PV and WP forecasting. Commencing with an introduction highlighting the significance of forecasting models in optimising renewable energy resource utilisation, the paper delves into various forecasting techniques and emphasises the critical need for data integrity and security. A comprehensive overview of non-Federated Learning-based PV and WP forecasting is presented based on high-quality journals, followed by in-depth discussions on specific non-Federated Learning approaches for each power source. The paper subsequently introduces FL and its variants, including Horizontal, Vertical, Transfer, Cross-Device, and Cross-Silo FL, highlighting the crucial role of encryption mechanisms and addressing associated challenges. Furthermore, drawing on extensive investigations of numerous pertinent articles, the paper outlines the innovative horizon of FL-based PV and wind power forecasting, offering insights into FL-based methodologies and concluding with observations drawn from this frontier. This review synthesises critical knowledge about PV and WP forecasting, leveraging the emerging paradigm of FL. Ultimately, this work contributes to the advancement of renewable energy integration and the optimisation of power grid management sustainably and securely.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/federated-learning-and-non-federated-learning-based-power-forecasting-of-photovoltaic-wind-power-energy-systems-a-systematic-review.pdf"
}

Minh Tuan Hua, Emil Mühlbradt Sveen, Siri Marte Schlanbusch and Filippo Sanfilippo. Robust-Adaptive Two-Loop Control for Robots with Mixed Rigid-Elastic Joints. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates. 2024, 11332–11339. URL PDF BibTeX

@inproceedings{hua2024robust,
	title = "Robust-Adaptive Two-Loop Control for Robots with Mixed Rigid-Elastic Joints",
	author = {Hua, Minh Tuan and Sveen, Emil M{\"u}hlbradt and Schlanbusch, Siri Marte and Sanfilippo, Filippo},
	booktitle = "Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Abu Dhabi, United Arab Emirates",
	pages = "11332--11339",
	year = 2024,
	url = "https://ieeexplore.ieee.org/document/10802178",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/robust-adaptive-two-loop-control-for-robots-with-mixed-rigid-elastic-joints.pdf"
}

Muhammad Hamza Zafar, Even Falkenberg Langas, Muhammad Faisal Aftab and Filippo Sanfilippo. Enhanced Intrusion Detection in Robot Operating Systems via Grid Search Based Multi-Head Attention Stacked Convolutional Network. In Proc. of the IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy. 2024, 3880-3885. PDF, DOI BibTeX

@inproceedings{10711785,
	author = "Zafar, Muhammad Hamza and Falkenberg Langas, Even and Aftab, Muhammad Faisal and Sanfilippo, Filippo",
	booktitle = "Proc. of the IEEE 20th International Conference on Automation Science and Engineering (CASE), Bari, Italy",
	title = "Enhanced Intrusion Detection in Robot Operating Systems via Grid Search Based Multi-Head Attention Stacked Convolutional Network",
	year = 2024,
	pages = "3880-3885",
	keywords = "Accuracy;Operating systems;Neural networks;Intrusion detection;Benchmark testing;Feature extraction;Security;Convolutional neural networks;Robots;Tuning;Intrusion Detection System;Robot Operating System;Multi-head Attention;Convolutional Neural Network",
	doi = "10.1109/CASE59546.2024.10711785",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/enhanced-intrusion-detection-in-robot-operating-systems-via-grid-search-based-multi-head-attention-stacked-convolutional-network.pdf"
}

Hareesh Chitikena, Irja Gravdahl, Kristin Ytterstad Pettersen, Alireza Mohammadi, Filippo Sanfilippo, Øyvind Stavdahl and Shugen Ma. Adaptive Manoeuvring Control for Planar Snake Robots in Uncertain Friction Environments. In Proc. of the American Control Conference (ACC), Toronto, Canada. 2024, 2844-2850. PDF, DOI BibTeX

@inproceedings{10644564,
	author = "Chitikena, Hareesh and Gravdahl, Irja and Pettersen, Kristin Ytterstad and Mohammadi, Alireza and Sanfilippo, Filippo and Stavdahl, Øyvind and Ma, Shugen",
	booktitle = "Proc. of the American Control Conference (ACC), Toronto, Canada",
	title = "Adaptive Manoeuvring Control for Planar Snake Robots in Uncertain Friction Environments",
	year = 2024,
	pages = "2844-2850",
	keywords = "Asymptotic stability;Parameter estimation;Friction;Simulation;Snake robots;Dynamics;Stability analysis",
	doi = "10.23919/ACC60939.2024.10644564",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Adaptive-Manoeuvring-Control-for-Planar-Snake-Robots-in-Uncertain-Friction-Environments.pdf"
}

Muhammad Hamza Zafar, Even Falkenberg LangÅs, Svein Olav Glesaaen Nyberg and Filippo Sanfilippo. Multimodal Fusion of EEG and EMG Signals Using Self-Attention Multi-Temporal Convolutional Neural Networks for Enhanced Hand Gesture Recognition in Rehabilitation. In Proc. of the IEEE International Conference on Omni-layer Intelligent Systems (COINS), London, United Kingdom. July 2024, 1-5. URL PDF, DOI BibTeX

@inproceedings{10622144,
	author = "Zafar, Muhammad Hamza and Lang{\aa}s, Even Falkenberg and Nyberg, Svein Olav Glesaaen and Sanfilippo, Filippo",
	booktitle = "Proc. of the IEEE International Conference on Omni-layer Intelligent Systems (COINS), London, United Kingdom",
	title = "Multimodal Fusion of EEG and EMG Signals Using Self-Attention Multi-Temporal Convolutional Neural Networks for Enhanced Hand Gesture Recognition in Rehabilitation",
	year = 2024,
	pages = "1-5",
	abstract = "In this work, we introduce an innovative approach to hand gesture recognition aimed at rehabilitation applications, utilising the synergistic potential of multimodal data fusion from electroencephalogram (EEG) and electromyogram (EMG) sensors. Our approach exploits the strength of Self-Attention Multi-Temporal Convolutional Networks (SAMTCN), which adeptly combine the distinct and complementary insights provided by EEG and EMG signals. The core of our methodology is the strategic application of self-attention mechanisms with multi-temporal convolutional architectures. This design choice allows our model to capture and analyse temporal patterns in multimodal data with unprecedented precision, significantly enhancing its ability to generalise to new, unseen data. The effectiveness of our approach is evidenced by the model's exceptional performance, achieving an accuracy of over 97% in recognising diverse hand gestures. This high level of accuracy highlights the model's potential to revolutionise how interactions are facilitated in rehabilitation contexts.",
	keywords = "electric potential;technological innovation;accuracy;gesture recognition;sensor fusion;brain modeling;electromyography",
	doi = "10.1109/COINS61597.2024.10622144",
	url = "https://doi.ieeecomputersociety.org/10.1109/COINS61597.2024.10622144",
	publisher = "IEEE Computer Society",
	address = "Los Alamitos, CA, USA",
	month = "jul",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Multimodal-Fusion-of-EEG-and-EMG-Signals-Using-Self-Attention Multi-Temporal Convolutional-Neural-Networks-for-Enhanced-Hand-Gesture-Recognition-in-Rehabilitation.pdf"
}

Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Noman Mujeeb Khan and Filippo Sanfilippo. FireNet: A Hybrid Deep Learning Approach for Enhanced Fire Detection in Remote Sensing Imagery. In Proc. of the Intelligent Systems Conference (IntelliSys), Amsterdam, Netherlands. 2024, 1–15. PDF BibTeX

@inproceedings{bukhari2024firenet,
	title = "FireNet: A Hybrid Deep Learning Approach for Enhanced Fire Detection in Remote Sensing Imagery",
	author = "Bukhari, Syed Muhammad Salman and Zafar, Muhammad Hamza and Moosavi, Syed Kumayl Raza and Khan, Noman Mujeeb and Sanfilippo, Filippo",
	booktitle = "Proc. of the Intelligent Systems Conference (IntelliSys), Amsterdam, Netherlands",
	pages = "1--15",
	year = 2024,
	organization = "Springer",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/FireNet-A-Hybrid-Deep-Learning-Approach-for-Enhanced-Fire-Detection-in-Remote-Sensing-Imagery.pdf"
}

Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Noman Mujeeb Khan and Filippo Sanfilippo. Enhancing Alzheimer’s Disease Detection and Classification Through Federated Learning-Optimized Deep Convolutional Neural Networks on MRI Data. In Proc. of the Intelligent Systems Conference (IntelliSys), Amsterdam, Netherlands. 2024, 693–712. PDF BibTeX

@inproceedings{bukhari2024enhancing,
	title = "Enhancing Alzheimer’s Disease Detection and Classification Through Federated Learning-Optimized Deep Convolutional Neural Networks on MRI Data",
	author = "Bukhari, Syed Muhammad Salman and Zafar, Muhammad Hamza and Moosavi, Syed Kumayl Raza and Khan, Noman Mujeeb and Sanfilippo, Filippo",
	booktitle = "Proc. of the Intelligent Systems Conference (IntelliSys), Amsterdam, Netherlands",
	pages = "693--712",
	year = 2024,
	organization = "Springer",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Enhancing-Alzheimers-Disease-Detection-and-Classification-through-Federated-Learning-Optimized-Deep-Convolutional-Neural-Networks-on-MRI-Data.pdf"
}

Minh Tuan Hua, Jong Hyeon Park and Filippo Sanfilippo. Modelling and Control of a Hybrid Robotic Arm with Mixed Rigid-Elastic Joints. In Proc. of the IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), Kristiansand, Norway. 2024, 1-6. PDF, DOI BibTeX

@inproceedings{10665130,
	author = "Hua, Minh Tuan and Park, Jong Hyeon and Sanfilippo, Filippo",
	booktitle = "Proc. of the IEEE 19th Conference on Industrial Electronics and Applications (ICIEA), Kristiansand, Norway",
	title = "Modelling and Control of a Hybrid Robotic Arm with Mixed Rigid-Elastic Joints",
	year = 2024,
	pages = "1-6",
	keywords = "Accuracy;Uncertainty;Service robots;Trajectory tracking;Heuristic algorithms;Dynamics;Position control",
	doi = "10.1109/ICIEA61579.2024.10665130",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Modelling-and-Control-of-a-Hybrid-Robotic-Arm-with-Mixed-Rigid-Elastic-Joints.pdf"
}

Muhammad Hamza Zafar, Syed Muhammad Salman Bukhari, Mohamad Abou Houran, Majad Mansoor, Noman Mujeeb Khan and Filippo Sanfilippo. DeepTimeNet: A novel architecture for precise surface temperature estimation of lithium-ion batteries across diverse ambient conditions. Case Studies in Thermal Engineering 61:105002, 2024. URL, DOI BibTeX

@article{ZAFAR2024105002,
	title = "DeepTimeNet: A novel architecture for precise surface temperature estimation of lithium-ion batteries across diverse ambient conditions",
	journal = "Case Studies in Thermal Engineering",
	volume = 61,
	pages = 105002,
	year = 2024,
	issn = "2214-157X",
	doi = "https://doi.org/10.1016/j.csite.2024.105002",
	url = "https://www.sciencedirect.com/science/article/pii/S2214157X24010335",
	author = "Muhammad Hamza Zafar and Syed Muhammad Salman Bukhari and Mohamad Abou Houran and Majad Mansoor and Noman Mujeeb Khan and Filippo Sanfilippo",
	keywords = "Battery management systems, Surface temperature estimation, Lithium-ion batteries, Deep neural networks, Time-series analysis, Predictive modelling, Temperature-dependent performance",
	abstract = "With the growing demand for battery-powered devices and electric vehicles, the need for improved battery performance and safety is paramount. A key determinant of battery health is the accurate monitoring of surface temperature (ST). Conventional ST estimation often depends on direct sensor measurements, which may not be cost-effective and can impact system reliability. This paper presents DeepTimeNet, a novel approach leveraging deep learning (DL) architectures for sensorless ST prediction in lithium-ion batteries. DeepTimeNet combines Convolutional Neural Networks (CNN), ResNet blocks, Inception modules, Bidirectional LSTM, and GRU layers to precisely model the time-dependent behaviour of batteries. A comprehensive evaluation against traditional models, across temperatures ranging from -20 °C to 25 °C and under various driving profiles, including US06 and Urban Dynamometer Driving Schedule (UDDS), is conducted. DeepTimeNet’s performance is quantified by metrics such as mean absolute error (MAE), surpassing that of models like Gated Recurrent Unit-Recurrent Neural Network (GRU-RNN), Convolutional Neural Network-Long Short Term Memory Network (CNN-LSTM), and Long Short Term Memory Network (LSTM). The results demonstrate DeepTimeNet’s superior performance, with an RMSE of 0.0971, MSE of 0.0099, MAE of 0.0912, and MAXE of 0.3963, validating it as an advanced tool for enhancing the efficacy of battery management systems and underscoring its potential as a benchmark for future innovations."
}

Opy Das, Muhammad Hamza Zafar, Filippo Sanfilippo, Souman Rudra and Mohan Lal Kolhe. Advancements in digital twin technology and machine learning for energy systems: A comprehensive review of applications in smart grids, renewable energy, and electric vehicle optimisation. Energy Conversion and Management: X 24:100715, 2024. URL, DOI BibTeX

@article{DAS2024100715,
	title = "Advancements in digital twin technology and machine learning for energy systems: A comprehensive review of applications in smart grids, renewable energy, and electric vehicle optimisation",
	journal = "Energy Conversion and Management: X",
	volume = 24,
	pages = 100715,
	year = 2024,
	issn = "2590-1745",
	doi = "https://doi.org/10.1016/j.ecmx.2024.100715",
	url = "https://www.sciencedirect.com/science/article/pii/S2590174524001934",
	author = "Opy Das and Muhammad Hamza Zafar and Filippo Sanfilippo and Souman Rudra and Mohan Lal Kolhe",
	keywords = "Digital twin, Machine learning, Smart Grid, Real-time data communication, Power system digital twin, Renewable energy, Electric vehicle",
	abstract = "The growing interest in Digital Twin (DT) Technology represents a significant advancement in academic research and industrial applications. Leveraging advancements in Internet of Things (IoT), sensors, and communication devices, DTs are increasingly utilised across different sectors, notably in the energy domain such as Power Systems and Smart Grids. DT concepts facilitate the creation of virtual models mirroring physical assets, streamlining real-time data management and analysis. Driven by the potential of DTs to revolutionise energy systems, this paper offers a comprehensive review of DT applications in the power sector, specifically within next-generation energy systems like Smart Grids. TThe integration of DT technology with Machine Learning (ML) algorithms is highlighted as a key factor in significantly enhancing the performance and capabilities of these advanced energy systems. In contrast to prior reviews, our study meticulously investigates all of the crucial components of energy systems, including forecasting, anomaly detection, and security, which are fundamental for improving the management of operational grids. In addition, the study examines the seamless incorporation of Renewable Energy into current grids and investigates how DT technology could contribute to Electric Vehicles for increased sustainability and reliability within the Smart Grid framework. This review underlines that DTs significantly enhance the management of real-time data and analysis, consequently improving operational grid management. There are ample opportunities into further research and development to design a more advanced and digital system as compared to conventional power systems. The findings are presented in clear and concise tables, highlighting current limitations, proposing effective solutions, and identifying potential future research directions in academia and industry."
}

Aitzaz Ahmed Murtaza, Amina Saher, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Muhammad Faisal Aftab and Filippo Sanfilippo. Paradigm shift for predictive maintenance and condition monitoring from Industry 4.0 to Industry 5.0: A systematic review, challenges and case study. Results in Engineering 24:102935, 2024. URL, DOI BibTeX

@article{AHMEDMURTAZA2024102935,
	title = "Paradigm shift for predictive maintenance and condition monitoring from Industry 4.0 to Industry 5.0: A systematic review, challenges and case study",
	journal = "Results in Engineering",
	volume = 24,
	pages = 102935,
	year = 2024,
	issn = "2590-1230",
	doi = "https://doi.org/10.1016/j.rineng.2024.102935",
	url = "https://www.sciencedirect.com/science/article/pii/S2590123024011903",
	author = "Aitzaz {Ahmed Murtaza} and Amina Saher and Muhammad {Hamza Zafar} and Syed {Kumayl Raza Moosavi} and Muhammad {Faisal Aftab} and Filippo Sanfilippo",
	keywords = "Industry 5.0, Predictive maintenance, Condition monitoring, Digital Twins, Machine Learning, Internet of Things, Sustainable industrial processes, Human-centric design, Resilience",
	abstract = "This paper examines the integration of Industry 5.0 principles with advanced predictive maintenance (PdM) and condition monitoring (CM) practices, based on Industry 4.0's enabling technologies. It provides a comprehensive review of the roles of Machine Learning (ML), Digital Twins (DT), the Internet of Things (IoT), and Big Data (BD) in transforming PdM and CM. The study proposes a six-layered framework designed to enhance sustainability, human-centricity, and resilience in industrial systems. This framework includes layers for data acquisition, processing, human-machine interfaces, maintenance execution, feedback, and resilience. A case study on a boiler feed-water pump is also presented which demonstrates the framework's potential benefits, such as reduced downtime, extended lifespan, real-time equipment monitoring and improved efficiency. The findings of this study emphasises the importance of integrating human intelligence with advanced technologies for a collaborative and adaptive industrial environment, and suggest areas for future research."
}

Muhammad Hamza Zafar, Even Falkenberg Langås and Filippo Sanfilippo. Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review. Robotics and Computer-Integrated Manufacturing 89:102769, 2024. URL, DOI BibTeX

@article{ZAFAR2024102769,
	title = "Exploring the synergies between collaborative robotics, digital twins, augmentation, and industry 5.0 for smart manufacturing: A state-of-the-art review",
	journal = "Robotics and Computer-Integrated Manufacturing",
	volume = 89,
	pages = 102769,
	year = 2024,
	issn = "0736-5845",
	doi = "https://doi.org/10.1016/j.rcim.2024.102769",
	url = "https://www.sciencedirect.com/science/article/pii/S0736584524000553",
	author = "Muhammad Hamza Zafar and Even Falkenberg Langås and Filippo Sanfilippo",
	keywords = "Digital twins, Industry 5.0, Deep learning, Augmentation, HRC",
	abstract = "Industry 5.0 aims at establishing an inclusive, smart and sustainable production process that encourages human creativity and expertise by leveraging enhanced automation and machine intelligence. Collaborative robotics, or “cobotics”,is a major enabling technology of Industry 5.0, which aspires at improving human dexterity by elevating robots to extensions of human capabilities and, ultimately, even as team members. A pivotal element that has the potential to operate as an interface for the teaming aspiration of Industry 5.0 is the adoption of novel technologies such as virtual reality (VR), augmented reality (AR), mixed reality (MR) and haptics, together known as “augmentation”. Industry 5.0 also benefit from Digital Twins (DTs), which are digital representations of a physical assets that serves as their counterpart — or twins. Another essential component of Industry 5.0 is artificial intelligence (AI), which has the potential to create a more intelligent and efficient manufacturing process. In this study, a systematic review of the state of the art is presented to explore the synergies between cobots, DTs, augmentation, and Industry 5.0 for smart manufacturing. To the best of the author’s knowledge, this is the first attempt in the literature to provide a comprehensive review of the synergies between the various components of Industry 5.0. This work aims at increasing the global efforts to realize the large variety of application possibilities offered by Industry 5.0 and to provide an up-to-date reference as a stepping-stone for new research and development within this field."
}

Filippo Sanfilippo, Martin Økter, Jørgen Dale, Hua Minh Tuan, Muhammad Hamza Zafar and Morten Ottestad. Open-source design of low-cost sensorised elastic actuators for collaborative prosthetics and orthotics. HardwareX 19:e00564, 2024. URL, DOI BibTeX

@article{SANFILIPPO2024e00564,
	title = "Open-source design of low-cost sensorised elastic actuators for collaborative prosthetics and orthotics",
	journal = "HardwareX",
	volume = 19,
	pages = "e00564",
	year = 2024,
	issn = "2468-0672",
	doi = "https://doi.org/10.1016/j.ohx.2024.e00564",
	url = "https://www.sciencedirect.com/science/article/pii/S2468067224000580",
	author = "Filippo Sanfilippo and Martin Økter and Jørgen Dale and Hua Minh Tuan and Muhammad Hamza Zafar and Morten Ottestad",
	keywords = "Elastic joint, Prosthetics, Orthotics, Open-source, Cobots",
	abstract = "Collaborative robots, or cobots, have become popular due to their ability to safely operate alongside humans in shared environments. These robots use compliant actuators as a key design element to prevent damage during unintended collisions. In prosthetic and orthotic applications, compliant actuators are crucial for ensuring user safety and comfort. However, most compliant cobots for these applications are excessively expensive and complex to construct. Our study introduces an innovative, cost-effective, and sensorised elastic actuator design tailored for prosthetics and orthotics. The design uses a modular approach and leverages 3D printing technology for rapid customisation, enabling efficient and affordable fabrication. Both hardware and software components are open-source, facilitating unrestricted access for students, researchers, and practitioners. Our design supports impedance and admittance control techniques, enhancing the system’s capabilities. Validation results show a standard deviation of 9.67 Nm between calculated and measured torque in impedance control and 0.2563 radians between calculated and measured angles in admittance control. This allows for improved adaptability to varying operational requirements in prosthetics and orthotics. By introducing this educational framework encompassing a low-cost, sensorised elastic actuator design, we aim to address the need for accessible solutions in the field of collaborative robotics for prosthetics and orthotics."
}

Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi and FIlippo Sanfilippo. Hierarchical Recurrent-Inception Residual Transformer (HRIRT) for Multi-Dimensional Hand Force Estimation using Force Myography Sensor. IEEE Sensors Letters ():1-4, 2024. PDF, DOI BibTeX

@article{10605060,
	author = "Zafar, Muhammad Hamza and Moosavi, Syed Kumayl Raza and Sanfilippo, FIlippo",
	journal = "IEEE Sensors Letters",
	title = "Hierarchical Recurrent-Inception Residual Transformer (HRIRT) for Multi-Dimensional Hand Force Estimation using Force Myography Sensor",
	year = 2024,
	volume = "",
	number = "",
	pages = "1-4",
	keywords = "Force;Estimation;Sensors;Transformers;Data models;Three-dimensional displays;Mathematical models;Hand Force Estimation;Human-Robot Collaboration (HRC);Force Myography Sensors;Real-Time Estimation;Model Interpretability",
	doi = "10.1109/LSENS.2024.3431433",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Hierarchical Recurrent-Inception Residual Transformer-HRIRT-for-Multi-Dimensional-Hand-Force-Estimation-using-Force-Myography-Sensor.pdf"
}

Algimantas Venčkauskas, Jevgenijus Toldinas, Nerijus Morkevičius and Filippo Sanfilippo. An Email Cyber Threat Intelligence Method Using Domain Ontology and Machine Learning. Electronics 13(14), 2024. URL, DOI BibTeX

@article{electronics13142716,
	author = "Venčkauskas, Algimantas and Toldinas, Jevgenijus and Morkevičius, Nerijus and Sanfilippo, Filippo",
	title = "An Email Cyber Threat Intelligence Method Using Domain Ontology and Machine Learning",
	journal = "Electronics",
	volume = 13,
	year = 2024,
	number = 14,
	article-number = 2716,
	url = "https://www.mdpi.com/2079-9292/13/14/2716",
	issn = "2079-9292",
	abstract = "Email is an excellent technique for connecting users at low cost. Spam emails pose the risk of collecting a user’s personal information by fooling them into clicking on a link or engaging in other fraudulent activities. Furthermore, when a spam message is delivered, the user may read the entire message before deciding it is spam and deleting it. Most approaches to email classification proposed by other authors use natural language processing (NLP) methods to analyze the content of email messages. One of the biggest shortcomings of NLP-based methods is their dependence on the language in which a message is written. To construct an effective email cyber threat intelligence (CTI) sharing framework, the privacy of a message’s content must be preserved. This article proposes a novel domain-specific ontology and method for emails that require only the metadata of email messages to be shared to preserve their privacy, making them applicable to solutions for sharing email CTI. To preserve privacy, a new semantic parser was developed for the proposed email domain-specific ontology to populate email metadata and create a dataset. Machine learning algorithms were examined, and experiments were conducted to identify and classify spam messages using the newly created dataset. Feature-ranking algorithms, chi-squared, ANOVA (analysis of variance), and Kruskal–Wallis tests were used. In all experiments, the kernel naïve Bayes model demonstrated acceptable results. The highest accuracy of 92.28% and an F1 score of 95.92% for recognizing spam email messages were obtained using the proposed domain-specific ontology, the newly developed semantic parser, and the created metadata dataset.",
	doi = "10.3390/electronics13142716"
}

Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Mohamad Abou Houran, Zakria Qadir, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Enhancing cybersecurity in Edge IIoT networks: An asynchronous federated learning approach with a deep hybrid detection model. Internet of Things 27:101252, 2024. URL, DOI BibTeX

@article{MUHAMMADSALMANBUKHARI2024101252,
	title = "Enhancing cybersecurity in Edge IIoT networks: An asynchronous federated learning approach with a deep hybrid detection model",
	journal = "Internet of Things",
	volume = 27,
	pages = 101252,
	year = 2024,
	issn = "2542-6605",
	doi = "https://doi.org/10.1016/j.iot.2024.101252",
	url = "https://www.sciencedirect.com/science/article/pii/S2542660524001938",
	author = "Syed {Muhammad Salman Bukhari} and Muhammad Hamza Zafar and Mohamad Abou Houran and Zakria Qadir and Syed {Kumayl Raza Moosavi} and Filippo Sanfilippo",
	keywords = "Cybersecurity, Federated learning, Industrial Internet of Things (IIoT), Network intrusion detection, Data privacy, Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU), Long Short-Term Memory (LSTM) networks, Asynchronous learning",
	abstract = "In the rapidly evolving field of the Industrial Internet of Things (IIoT), advancements in wireless technology have resulted in significant cybersecurity vulnerabilities. These weaknesses pose serious risks such as damage to manufacturing systems, theft of intellectual property, and substantial financial losses. This study introduces an advanced deep hybrid learning model in an asynchronous federated learning setup, aimed at improving the detection of cyberattacks and ensuring robust data privacy. The combination of Convolutional Neural Networks (CNN), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM) networks provides an effective solution for quickly identifying anomalies in IIoT sensor traffic. Our model operates asynchronously, ensuring data remains localised to improve security while avoiding the need for complete node synchronisation. Demonstrating outstanding effectiveness, the model achieves an accuracy of 1.00%, precision of 1.00%, recall of 1.00%, and an F1 score of 1.00% across a variety of IIoT environments. These results highlight the model’s exceptional adaptability and its capability to rapidly respond to emergent threats, marking a significant step forward in the protection of IIoT infrastructures and the rigorous maintenance of data privacy."
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, Ahsan Saadat, Zainab Abaid, Wei Ni, Abbas Jamalipour and Filippo Sanfilippo. Transductive Transfer Learning-Assisted Hybrid Deep Learning Model for Accurate State of Charge Estimation of Li-Ion Batteries in Electric Vehicles. IEEE Transactions on Intelligent Transportation Systems, 2024. URL PDF, DOI BibTeX

@article{moosavi2024transductive,
	title = "Transductive Transfer Learning-Assisted Hybrid Deep Learning Model for Accurate State of Charge Estimation of Li-Ion Batteries in Electric Vehicles",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Saadat, Ahsan and Abaid, Zainab and Ni, Wei and Jamalipour, Abbas and Sanfilippo, Filippo",
	journal = "IEEE Transactions on Intelligent Transportation Systems",
	year = 2024,
	publisher = "IEEE",
	abstract = "Accurate estimation of the State of Charge (SoC) of Li-Ion batteries is crucial for secure and efficient energy consumption in electric vehicles (EVs). Traditional SoC estimation methods often require expert knowledge of battery chemistry and suffer from limited accuracy due to complex non-linear battery behaviour. Owing to the model-free nature and enhanced ability of non-linear regression in deep learning (DL), this paper proposes a hybrid DL model trained by a novel metaheuristic technique, namely the Hybrid Sine Cosine Firehawk Algorithm (HSCFHA). The proposed method utilises the Transductive Transfer Learning (TTL) technique to leverage the intrinsic relationship between different real-world datasets to estimate the SoC of batteries accurately. The evaluation analysis includes three diverse datasets of EV charging drive cycles: the Highway Fuel Economy Test Cycle (HWFET), Highway Driving Schedule (US06) and Urban Dynamometer Driving Schedule (UDDS), at various temperatures of $0^\circ$C, $10^\circ$C, and $25^\circ$C. The considered evaluation metrics, i.e., Normal Mean Squared Error (NMSE), Root Mean Squared Error (RMSE), and $R^2$, achieve values of 0.091\%, 0.087\%, and 99.51\%, respectively. The TTL-HSCFHA-DNN effectively produces higher accuracy with a time-efficient convergence rate, compared to existing methods. The approach enables EV systems to operate more efficiently with improved battery life.",
	doi = "https://doi.org/10.1109/TITS.2024.3403518",
	url = "https://ieeexplore.ieee.org/document/10546330",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Transductive_Transfer_Learning-Assisted_Hybrid_Deep_Learning_Model_for_Accurate_State_of_Charge_Estimation_of_Li-Ion_Batteries_in_Electric_Vehicles.pdf"
}

Hareesh Chitikena, Alireza Mohammadi, Filippo Sanfilippo and Mohammad Poursina. Anisotropic Friction Skin for Holonomic Snake Robot Mobility. In Proc. of the IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), Hong Kong, China. 2024, 222–227. URL PDF BibTeX

@inproceedings{chitikena2024anisotropic,
	title = "Anisotropic Friction Skin for Holonomic Snake Robot Mobility",
	author = "Chitikena, Hareesh and Mohammadi, Alireza and Sanfilippo, Filippo and Poursina, Mohammad",
	booktitle = "Proc. of the IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), Hong Kong, China",
	pages = "222--227",
	year = 2024,
	abstract = "Achieving effective locomotion for holonomic snake robots in diverse terrains for Search and Rescue (SAR) poses a significant challenge. While biological snakes exhibit complex mobility with the aid of anisotropic skin and a flexible body, replicating such capabilities in robotic systems demands specialised design considerations. This paper addresses designing and analysing anisotropic frictional skin to enhance the locomotion of holonomic snake robots in flat, variably friction environments. Two distinct frictional skins are developed and analysed through a peristaltic dynamic model. Moreover, comprehensive testing is conducted on various substrates to assess the effectiveness of the designed snakeskins. Experimental results indicate that a snake robot equipped with an interlocking-based skin on an Expanded Polystyrene substrate achieves small forward locomotion, while a Molecular Interaction-based skin enables sideways motion. This study provides insights into preliminary skin designs and locomotion tests conducted on flat surfaces, emphasising the need for further refinement to meet the demands of SAR applications.",
	url = "https://ieeexplore.ieee.org/document/10557914",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Anisotropic-Friction-Skin-for-Holonomic-Snake-Robot-Mobility.pdf"
}

Even Falkenberg LangÅs, Muhammad Hamza Zafar, Svein Olav Nyberg and Filippo Sanfilippo. Human Trajectory Simulation in Industrial Settings Using the Ornstein-Uhlenbeck Process and Deep Learning Based Classification. In Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece. 2024, 427–432. URL PDF BibTeX

@inproceedings{langaas2024human,
	title = "Human Trajectory Simulation in Industrial Settings Using the Ornstein-Uhlenbeck Process and Deep Learning Based Classification",
	author = "Lang{\aa}s, Even Falkenberg and Zafar, Muhammad Hamza and Nyberg, Svein Olav and Sanfilippo, Filippo",
	booktitle = "Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece",
	pages = "427--432",
	year = 2024,
	abstract = "This paper presents a novel method of simulating human trajectories using the Ornstein-Uhlenbeck (OU) process in addition to deep learning (DL) based classification. The OU process is a stochastic process and is used in this paper to simulate the movement of a person on a typical factory floor. This work aims at developing systems that increase machines' awareness of people and make predictions about their behaviour to improve efficiency and safety in industrial settings. Sequences of simulated 2D coordinates of people moving on the factory floor are generated. Successively, these synthetic data are used to classify the path that the human is following, using a stacked long short-term memory (LSTM) network and a stacked bidirectional LSTM (BiLSTM) network. The results from this study suggest that, for such applications, it should be possible to predict future movements in 2D for human-robot collaboration (HRC) and teaming (HRT).",
	url = "https://ieeexplore.ieee.org/document/10553211",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Human-Trajectory-Simulation-in-Industrial-Settings-Using-the-Ornstein-Uhlenbeck-Process-and-Deep-Learning-Based-Classification.pdf"
}

Muhammad Hamza Zafar, Even Falkenberg LangÅs and Filippo Sanfilippo. Real-Time Gesture-Based Control of a Quadruped Robot Using a Stacked Convolutional Bi-Long Short-Term Memory (Bi-LSTM) Neural Network. In Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece. 2024, 81–86. URL PDF BibTeX

@inproceedings{zafar2024real,
	title = "Real-Time Gesture-Based Control of a Quadruped Robot Using a Stacked Convolutional Bi-Long Short-Term Memory (Bi-LSTM) Neural Network",
	author = "Zafar, Muhammad Hamza and Lang{\aa}s, Even Falkenberg and Sanfilippo, Filippo",
	booktitle = "Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece",
	pages = "81--86",
	year = 2024,
	abstract = "In recent years, advancements in robotics have driven a growing interest in enhancing human-robot interaction (HRI) for improved collaboration and effectiveness, particularly in critical scenarios like search and rescue (SAR) operations. This paper introduces an innovative approach for intuitive control of a quadruped robot, MiT Spot Robot, through hand gestures, using a Stacked Convolutional Bi-Long Short-Term Memory (Bi-LSTM) neural network model. To enable seamless and efficient human-robot interaction (HRI), this advanced model is integrated with the Robot Operating System (ROS) and the Gazebo simulation environment. We propose a robust hand gesture recognition system employing computer vision techniques that accurately interpret dynamic hand gestures in real time. The recognised gestures are mapped to specific locomotion and task commands, facilitating natural and intuitive control of the Quadruped Robot during search and rescue (SAR) operations. A comprehensive hyperparameter tuning approach using a grid search is implemented to optimise the model's performance. Our simulation-based experimentation in ROS/Gazebo validates the effectiveness and responsiveness of the proposed control scheme, showcasing its potential to enhance human-robot collaboration (HRC) in critical scenarios such as SAR missions.",
	url = "https://ieeexplore.ieee.org/document/10553163",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Real-Time-Gesture-based-Control-of-a-Quadruped-Robot-using-a-Stacked-Convolutional-Bi-Long-Short-Term-Memory-Bi-LSTM-Neural-Network.pdf"
}

Minh Tuan Hua, Mohammad Poursina and Filippo Sanfilippo. Dynamic Modelling of Mixed Rigid-Flexible Joint Robotic Manipulator Using Recursive Newton-Euler Formulation. In Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece. 2024, 165–171. URL PDF BibTeX

@inproceedings{hua2024dynamic,
	title = "Dynamic Modelling of Mixed Rigid-Flexible Joint Robotic Manipulator Using Recursive Newton-Euler Formulation",
	author = "Hua, Minh Tuan and Poursina, Mohammad and Sanfilippo, Filippo",
	booktitle = "Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece",
	pages = "165--171",
	year = 2024,
	abstract = "Rigid joints have good position control accuracy due to their stiffness. On the other hand, elastic joints are advantageous when interacting with the environment due to their compliance characteristics. Most of the current robot arms use all rigid joints or all elastic joints in their designs. This work presents a highly efficient approach to formulate both inverse and forward dynamics of robots with mixed rigid-elastic joints using recursive Newton-Euler algorithm. To simplify the modelling process, a unified rigid body is proposed, where the link and all motors attached to it are unified as a whole unyielding entity. In addition, the effect of gear ratio is considered in the development of this modelling approach. Successively, an inverse dynamics controller is presented. Finally, simulations are conducted based on the proposed modelling method and the inverse dynamics control algorithm.",
	url = "https://ieeexplore.ieee.org/document/10553136",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Dynamic-Modelling-of-Mixed-Rigid-Flexible-Joint-Robotic-Manipulator-Using-Recursive-Newton-Euler-Formulation.pdf"
}

Filippo Sanfilippo, Martin Økter, Jørgen Dale, Hua Minh Tuan and Morten Ottestad. Revolutionising Prosthetics and Orthotics with Affordable Customisable Open-Source Elastic Actuators. In Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece. 2024, 57–63. URL PDF BibTeX

@inproceedings{sanfilippo2024revolutionising,
	title = "Revolutionising Prosthetics and Orthotics with Affordable Customisable Open-Source Elastic Actuators",
	author = "Sanfilippo, Filippo and {\O}kter, Martin and Dale, J{\o}rgen and Tuan, Hua Minh and Ottestad, Morten",
	booktitle = "Proc. of the 10th IEEE International Conference on Automation, Robotics and Applications (ICARA), Athens, Greece",
	pages = "57--63",
	year = 2024,
	abstract = "Collaborative robots, also known as cobots, have become progressively popular as they are designed to safely work alongside humans or in shared environments. The adoption of compliant actuators, which avoid damage in the event of an unintentional collision, is an important feature of their design. In prosthetic and orthotic applications, the use of compliant actuators, which minimise damage in the case of an inadvertent contact, is critical to ensuring safety and comfort for the user. In dynamic settings, elastic actuators are preferred over rigid ones, however most compliant cobots are currently too expensive or complex to construct for prosthetic and orthotic applications. To address this challenge, this study presents a low-cost sensorised elastic actuator design for prosthetics and orthotics. This is presented as an educational framework. The design is modular and can be quickly customised using 3D printing technology, allowing for efficient and cost-effective fabrication. Both the hardware and software are open-source, enabling easy access for students, researchers and practitioners. The design also allows for the introduction of impedance and admittance control techniques, providing even greater versatility to the system.",
	url = "https://ieeexplore.ieee.org/document/10553120",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Revolutionising-Prosthetics-and-Orthotics-with-Affordable-Customisable-Open-Source-Elastic-Actuators.pdf"
}

Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Enhancing unmanned ground vehicle performance in SAR operations: integrated gesture-control and deep learning framework for optimised victim detection. Frontiers in robotics and AI 11:1356345, 2024. DOI BibTeX

@article{zafar2024enhancing,
	title = "Enhancing unmanned ground vehicle performance in SAR operations: integrated gesture-control and deep learning framework for optimised victim detection",
	author = "Zafar, Muhammad Hamza and Moosavi, Syed Kumayl Raza and Sanfilippo, Filippo",
	journal = "Frontiers in robotics and AI",
	volume = 11,
	pages = 1356345,
	year = 2024,
	publisher = "Frontiers Media SA",
	abstract = "In this study, we address the critical need for enhanced situational awareness and victim detection capabilities in Search and Rescue (SAR) operations amidst disasters. Traditional unmanned ground vehicles (UGVs) often struggle in such chaotic environments due to their limited manoeuvrability and the challenge of distinguishing victims from debris. Recognising these gaps, our research introduces a novel technological framework that integrates advanced gesture-recognition with cutting-edge deep learning for camera-based victim identification, specifically designed to empower UGVs in disaster scenarios. At the core of our methodology is the development and implementation of the Meerkat Optimization Algorithm—Stacked Convolutional Neural Network—Bi—Long Short Term Memory—Gated Recurrent Unit (MOA-SConv-Bi-LSTM-GRU) model, which sets a new benchmark for hand gesture detection with its remarkable performance metrics: accuracy, precision, recall, and F1-score all approximately 0.9866. This model enables intuitive, real-time control of UGVs through hand gestures, allowing for precise navigation in confined and obstacle-ridden spaces, which is vital for effective SAR operations. Furthermore, we leverage the capabilities of the latest YOLOv8 deep learning model, trained on specialised datasets to accurately detect human victims under a wide range of challenging conditions, such as varying occlusions, lighting, and perspectives. Our comprehensive testing in simulated emergency scenarios validates the effectiveness of our integrated approach. The system demonstrated exceptional proficiency in navigating through obstructions and rapidly locating victims, even in environments with visual impairments like smoke, clutter, and poor lighting. Our study not only highlights the critical gaps in current SAR response capabilities but also offers a pioneering solution through a synergistic blend of gesture-based control, deep learning, and purpose-built robotics. The key findings underscore the potential of our integrated technological framework to significantly enhance UGV performance in disaster scenarios, thereby optimising life-saving outcomes when time is of the essence. This research paves the way for future advancements in SAR technology, with the promise of more efficient and reliable rescue operations in the face of disaster.",
	doi = "https://doi.org/10.3389/frobt.2024.1356345"
}

Diana Irinel Baila, Filippo Sanfilippo, Tom Savu, Filip Górski, Ionut Cristian Radu, Catalin Zaharia, Constantina Anca Parau, Martin Zelenay and Pacurar Razvan. 3D printing of personalised stents using new advanced photopolymerizable resins and Ti-6Al-4V alloy. Rapid Prototyping Journal, 2024. URL BibTeX

@article{baila20243d,
	title = "3D printing of personalised stents using new advanced photopolymerizable resins and Ti-6Al-4V alloy",
	author = "Baila, Diana Irinel and Sanfilippo, Filippo and Savu, Tom and G{\'o}rski, Filip and Radu, Ionut Cristian and Zaharia, Catalin and Parau, Constantina Anca and Zelenay, Martin and Razvan, Pacurar",
	journal = "Rapid Prototyping Journal",
	year = 2024,
	publisher = "Emerald Publishing Limited",
	url = "https://www.emerald.com/insight/content/doi/10.1108/RPJ-10-2023-0360/full/html"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. Collaborative robots (cobots) for disaster risk resilience: a framework for swarm of snake robots in delivering first aid in emergency situations. Frontiers in Robotics and AI 11, 2024. URL, DOI BibTeX

@article{10.3389/frobt.2024.1362294,
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	title = "Collaborative robots (cobots) for disaster risk resilience: a framework for swarm of snake robots in delivering first aid in emergency situations",
	journal = "Frontiers in Robotics and AI",
	volume = 11,
	year = 2024,
	url = "https://www.frontiersin.org/articles/10.3389/frobt.2024.1362294",
	doi = "10.3389/frobt.2024.1362294",
	issn = "2296-9144",
	abstract = "Cobots are robots that are built for human-robot collaboration (HRC) in a shared environment. In the aftermath of disasters, cobots can cooperate with humans to mitigate risks and increase the possibility of rescuing people in distress. This study examines the resilient and dynamic synergy between a swarm of snake robots, first responders and people to be rescued. The possibility of delivering first aid to potential victims dispersed around a disaster environment is implemented. In the HRC simulation framework presented in this study, the first responder initially deploys a UAV, swarm of snake robots and emergency items. The UAV provides the first responder with the site planimetry, which includes the layout of the area, as well as the precise locations of the individuals in need of rescue and the aiding goods to be delivered. Each individual snake robot in the swarm is then assigned a victim. Subsequently an optimal path is determined by each snake robot using the A* algorithm, to approach and reach its respective target while avoiding obstacles. By using their prehensile capabilities, each snake robot adeptly grasps the aiding object to be dispatched. The snake robots successively arrive at the delivering location near the victim, following their optimal paths, and proceed to release the items. To demonstrate the potential of the framework, several case studies are outlined concerning the execution of operations that combine locomotion, obstacle avoidance, grasping and deploying. The Coppelia-Sim Robotic Simulator is utilised for this framework. The analysis of the motion of the snake robots on the path show highly accurate movement with and without the emergency item. This study is a step towards a holistic semi-autonomous search and rescue operation."
}

Muhammad Hamza Zafar, Noman Mujeeb Khan, Mohamad Abou Houran, Majad Mansoor, Naureen Akhtar and Filippo Sanfilippo. A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature. Energy 292:130584, 2024. URL, DOI BibTeX

@article{ZAFAR2024130584,
	title = "A novel hybrid deep learning model for accurate state of charge estimation of Li-Ion batteries for electric vehicles under high and low temperature",
	journal = "Energy",
	volume = 292,
	pages = 130584,
	year = 2024,
	issn = "0360-5442",
	doi = "https://doi.org/10.1016/j.energy.2024.130584",
	url = "https://www.sciencedirect.com/science/article/pii/S0360544224003566",
	author = "Muhammad Hamza Zafar and Noman Mujeeb Khan and Mohamad Abou Houran and Majad Mansoor and Naureen Akhtar and Filippo Sanfilippo",
	keywords = "State of charge, Electric vehicles, Deep learning, Evolutionary intelligence, High and low temperatures",
	abstract = "This paper presents a novel architecture, termed Fusion-Fission Optimisation (FuFi) based Convolutional Neural Network with Bi-Long Short Term Memory Network (FuFi-CNN-Bi-LSTM), to enhance state of charge (SoC) estimation performance. The proposed FuFi-CNN-Bi-LSTM model leverages the power of both Convolutional Neural Networks (CNN) and Bi-Long Short Term Memory Networks (Bi-LSTM) while utilizing FuFi optimization to effectively tune the hyperparameters of the network. This optimization technique facilitates efficient SoC estimation by finding the optimal configuration of the model. A comparative analysis is conducted against FuFi Algorithm-based models, including FuFi-CNN-LSTM, FuFi-Bi-LSTM, FuFi-LSTM, and FuFi-CNN. The comparison involves assessing performance on SoC estimation tasks and identifying the strengths and limitations of models. Furthermore, the proposed FuFi-CNN-Bi-LSTM model undergoes rigorous testing on various drive cycle tests, including HPPC, HWFET, UDDS, and US06, at different temperatures ranging from -20 to 25 degrees Celsius. The model’s robustness and reliability are assessed under different real-world operating conditions using well-established evaluation indexes, including Relative Error (RE),Mean Absolute Error (MAE), R Square (R2), and Granger Causality Test. The results demonstrate that the proposed FuFi-CNN-Bi-LSTM model achieves efficient SoC estimation performance across a wide range of temperatures at higher and lower ranges. This finding signifies the model’s efficacy in accurately estimating SoC in various operating conditions."
}

Răzvan Ioan Păcurar, Filippo Sanfilippo, Martin Bjaadal Økter, Diana-Irinel Băilă, Cătălin Zaharia, Adrian Ionuţ Nicoară, Ionuț Cristian Radu, Tom Savu, Filip Górski, Wiesław Kuczko, Radosław Wichniarek, Dan Sorin Comşa, Martin Zelenay and Paweł Woźniak. Use of high-performance polymeric materials in customized low-cost robotic grippers for biomechatronic applications: experimental and analytical research. Frontiers in Materials 11, 2024. URL, DOI BibTeX

@article{10.3389/fmats.2024.1304339,
	author = "Păcurar, Răzvan Ioan and Sanfilippo, Filippo and Økter, Martin Bjaadal and Băilă, Diana-Irinel and Zaharia, Cătălin and Nicoară, Adrian Ionuţ and Radu, Ionuț Cristian and Savu, Tom and Górski, Filip and Kuczko, Wiesław and Wichniarek, Radosław and Comşa, Dan Sorin and Zelenay, Martin and Woźniak, Paweł",
	title = "Use of high-performance polymeric materials in customized low-cost robotic grippers for biomechatronic applications: experimental and analytical research",
	journal = "Frontiers in Materials",
	volume = 11,
	year = 2024,
	url = "https://www.frontiersin.org/articles/10.3389/fmats.2024.1304339",
	doi = "10.3389/fmats.2024.1304339",
	issn = "2296-8016",
	abstract = "Advancements in materials science and 3D printing technologies have opened up new avenues for developing low-cost robotic grippers with high-performance capabilities, making them suitable for various biomechatronic applications. In this research, it has been explored the utilization of high-performance polymer materials, such as Polyetherketoneketone (PEKK), Polyethylene Terephthalate Glycol (PET-G) and MED 857 (DraftWhite), in the designing and developing of customized robotic grippers. The primary focus of made analyses was oriented on materials characterization, both experimentally and analytically. Computer-Aided Engineering (CAE) methods were employed to simulate bending experiments, allowing for a comprehensive analysis of the mechanical behavior of the selected materials. These simulations were validated through physical bending experiments using samples fabricated via 3D printing technologies, including Fused Filament Fabrication (FFF) for PET-G and PEKK, as well as Jetted Photopolymer (PolyJet) technology employing UV Resin for MED 857. The findings of this research provided advantages of utilizing advanced materials like PEKK in low-cost robotic grippers for biomechatronic applications. The experimental and analytical approaches offer valuable insights into material selection, design optimization, and the development of cost-effective high-performing robotic systems with a wide range of applications in the field of biomechatronics."
}

Syed Muhammad Salman Bukhari, Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, Majad Mansoor, Hassan Mohyuddin, Syed Sajid Ullah, Roobaea Alroobaea and Filippo Sanfilippo. Federated transfer learning with orchard-optimized Conv-SGRU: A novel approach to secure and accurate photovoltaic power forecasting. Renewable Energy Focus 48:100520, 2024. URL, DOI BibTeX

@article{MUHAMMADSALMANBUKHARI2024100520,
	title = "Federated transfer learning with orchard-optimized Conv-SGRU: A novel approach to secure and accurate photovoltaic power forecasting",
	journal = "Renewable Energy Focus",
	volume = 48,
	pages = 100520,
	year = 2024,
	issn = "1755-0084",
	doi = "https://doi.org/10.1016/j.ref.2023.100520",
	url = "https://www.sciencedirect.com/science/article/pii/S1755008423001163",
	author = "Syed {Muhammad Salman Bukhari} and Syed {Kumayl Raza Moosavi} and Muhammad {Hamza Zafar} and Majad Mansoor and Hassan Mohyuddin and Syed {Sajid Ullah} and Roobaea Alroobaea and Filippo Sanfilippo",
	keywords = "Privacy-preserving, FL, TL, PV power forecasting, Deep learning",
	abstract = "Accurate photovoltaic (PV) power forecasting is pivotal for optimizing the integration of RES into the grid and guaranteeing proficient energy management. Concurrently, the sensitive nature of data obtained from individual PV systems underscores paramount concerns regarding data privacy and security. In this manuscript, we introduce an innovative approach for PV power forecasting that addresses these concerns, deploying federated learning (FL) combined with TL. This is orchestrated via a hybrid deep learning model, denominated as Federated transfer learning (TL) Convolutional Neural Network with Stacked Gated Recurrent Unit (FL-TL-Conv-SGRU). To optimize the performance of the Conv-SGRU model, we employ the OA for hyperparameter tuning, a novel bio-inspired technique inspired by orchard gardening practices. This algorithm presents a distinctive interplay between exploration and exploitation in the hyperparameter space, potentially elevating the model’s performance. Our exposition covers eight disparate datasets from PV systems, which are judiciously split into two cohorts, safeguarding data privacy. Through the prism of FL, we ensure data security by orchestratively training the Conv-SGRU model over distributed datasets. This strategy allows tapping into the shared wisdom across the datasets, all the while ascertaining individual data remains localized, boosting model generalization and predictive prowess. Additionally, TL is invoked to benefit from pre-trained feature representations, facilitating effective knowledge transmission across diverse PV setups with unique characteristics and locales. The put-forth FL-TL-Conv-SGRU design amalgamates the essence of FL, TL, convolutional neural networks, and stacked gated recurrent units. This ensemble aids in deciphering spatial–temporal intricacies intrinsic to PV power generation. Through empirical analyses, we evince that our FL-TL-Conv-SGRU model transcends conventional forecasting paradigms, emphasizing its adeptness in delivering meticulous forecasts over a range of PV installations. Our results accentuate the bifurcated importance of the federated TL framework: a capability for collaborative training with an unwavering commitment to data privacy, and a proficiency in exploiting decentralized data. This strategy is particularly salient given the shifting regulatory milieu centered on data safeguarding and confidentiality. As we transition towards a world more reliant on renewable energy, our proposed stratagem promises to be a cornerstone for efficient, sustainable energy management, heralding a future replete with green energy."
}

Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Mohamad Abou Houran, Syed Kumayl Raza Moosavi, Majad Mansoor, Muhammad Muaaz and Filippo Sanfilippo. Secure and privacy-preserving intrusion detection in wireless sensor networks: Federated learning with SCNN-Bi-LSTM for enhanced reliability. Ad Hoc Networks 155:103407, 2024. URL, DOI BibTeX

@article{bukhari2024secure,
	title = "Secure and privacy-preserving intrusion detection in wireless sensor networks: Federated learning with SCNN-Bi-LSTM for enhanced reliability",
	journal = "Ad Hoc Networks",
	volume = 155,
	pages = 103407,
	year = 2024,
	issn = "1570-8705",
	doi = "https://doi.org/10.1016/j.adhoc.2024.103407",
	url = "https://www.sciencedirect.com/science/article/pii/S1570870524000180",
	author = "Syed Muhammad Salman Bukhari and Muhammad Hamza Zafar and Mohamad Abou Houran and Syed Kumayl Raza Moosavi and Majad Mansoor and Muhammad Muaaz and Filippo Sanfilippo",
	keywords = "WSNs, Network intrusion detection, Federated learning, Denial of Service, SCNN-Bi-LSTM, Stacked CNN",
	abstract = "As the digital landscape expands rapidly due to technological advancements, cybersecurity concerns have become more prevalent. Intrusion Detection Systems (IDSs), which are crucial for identifying unusual network traffic indicative of malicious activity, have become a necessity. These systems can be either hardware or software-based. However, traditional IDS models often fail to adequately protect data privacy and detect complex, unique breaches, particularly within Wireless Sensor Networks (WSNs). To address these limitations, this paper proposes a novel Stacked Convolutional Neural Network and Bidirectional Long Short Term Memory (SCNN-Bi-LSTM) model for intrusion detection in WSNs. This model leverages Federated Learning (FL) to enhance intrusion detection performance and safeguard privacy. The FL-based SCNN-Bi-LSTM model is unique in its approach, allowing multiple sensor nodes to collaboratively train a central global model without revealing private data, thereby alleviating privacy concerns. The deep learning methodology of the SCNN-Bi-LSTM model effectively identifies sophisticated and previously unknown cyber threats by meticulously examining both local and temporal linkages in network patterns. The model has been specifically designed to detect and categorize different types of Denial of Service (DoS) attacks using specialized WSN-DS and CIC-IDS-2017 datasets. Compared to traditional Artificial Deep Neural Network (ADNN) models, our proposed FL-SCNN-Bi-LSTM model demonstrated superior detection rates for complex and unknown attacks, significantly improving IDS performance. The model achieved a notable classification accuracy of approximately 99.9% precision and recall on both datasets, substantially reducing false positives and negatives. Our research underscores the potential of federated learning and deep learning in enhancing the security and privacy of WSNs. The proposed FL-SCNN-Bi-LSTM architecture not only facilitates the identification of complex cyber threats but also exemplifies how deep learning techniques can be employed to bolster intrusion detection systems while preserving user data privacy."
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. Collaborative Robots (Cobots) for Emergency Situations: a Snake Robots as a Team Member for Delivering First Aid in Emergency Situations. In Proceeding of the 57th Hawaii International Conference on System Sciences (HICSS 2024), Honolulu, Hawaii, United States of America. 2024, 443–452. URL BibTeX

@inproceedings{sanfilippo-2024-snake-team-member,
	title = "Collaborative Robots (Cobots) for Emergency Situations: a Snake Robots as a Team Member for Delivering First Aid in Emergency Situations",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 57th Hawaii International Conference on System Sciences (HICSS 2024), Honolulu, Hawaii, United States of America",
	pages = "443--452",
	year = 2024,
	abstract = "Cobots are robots that are built for human-robot collaboration (HRC) in a shared environment. In the aftermath of disasters, cobots can work with humans to reduce risk and increase the possibility of rescuing people. In this work, the collaboration between a snake robot, first responders and people to be rescued is considered. The possibility of delivering first aid to a victim is implemented. The snake robot receives (from first responders or another robot) the site planimetry, the location of the person to be rescued, and a aiding good to be delivered. The snake robot plans the path to reach the victim. By using its prehensile capabilities, the snake robot grasps the aiding object to be dispatched. Consequently, the snake robot reaches the delivering location and releases the item. To demonstrate the potential of the framework, several case studies are outlined concerning the execution of operations that combine locomotion and grasping.",
	url = "https://hdl.handle.net/10125/106428"
}

Filip Górski, Aleksandra Grohs, Wiesław Kuczko, Magdalena Żukowska, Radosław Wichniarek, Sabina Siwiec, Diana-Irinel Băilă, Martin Zelenay, Răzvan Păcurar and Filippo Sanfilippo. Development and Studies of VR-Assisted Hand Therapy Using a Customized Biomechatronic 3D Printed Orthosis. Electronics 13(1), 2024. URL, DOI BibTeX

@article{electronics13010079,
	author = "Górski, Filip and Grohs, Aleksandra and Kuczko, Wiesław and Żukowska, Magdalena and Wichniarek, Radosław and Siwiec, Sabina and Băilă, Diana-Irinel and Zelenay, Martin and Păcurar, Răzvan and Sanfilippo, Filippo",
	title = "Development and Studies of VR-Assisted Hand Therapy Using a Customized Biomechatronic 3D Printed Orthosis",
	journal = "Electronics",
	volume = 13,
	year = 2024,
	number = 1,
	article-number = 79,
	url = "https://www.mdpi.com/2079-9292/13/1/79",
	issn = "2079-9292",
	abstract = "This article presents the process of development, testing, and use of wrist–hand orthosis in the hand therapy of a teen patient with congenital paresis disease. A regular 3D-printed anatomically adjusted orthosis is modified with a set of sensors, to work as motion and interaction controller in virtual reality (VR). As the patient with this condition cannot operate VR controllers due to wrist and hand defects, the corrective orthosis was converted to a VR controller, by introducing custom-made electronics and commercially available motion trackers, linking them to the orthosis. A VR game scenario, with typical input from the VR controllers replaced by input from the custom-made controllers is then designed. The VR game scenario is prepared with involvement of physiotherapists, to incorporate the most important exercises for patients with the same condition. The scenario is tested with a group of human patients and assessed by an expert physiotherapist, for determining its efficiency, as well as to determine a set of necessary improvements for future development of the orthosis.",
	doi = "10.3390/electronics13010079"
}

Even Falkenberg LangÅs, Muhammad Hamza Zafar and Filippo Sanfilippo. Harnessing Digital Twins for Human-Robot Teaming in Industry 5.0: Exploring the Ethical and Philosophical Implications. In Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-human-robot-teaming-ethics,
	title = "Harnessing Digital Twins for Human-Robot Teaming in Industry 5.0: Exploring the Ethical and Philosophical Implications",
	author = "Lang{\aa}s, Even Falkenberg and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico",
	pages = "--",
	year = 2023,
	abstract = "In the era of Industry 5.0, the convergence of humans and robots in collaborative work environments has brought forth the concept of digital twins (DTs) of humans and robots. These virtual replicas, mirroring their physical counterparts, have become integral to the design and operation of complex systems. This paper aims to explore the ethical and philosophical implications associated with the design and use of DTs of humans and robots in human-robot collaboration (HRC), and even further in human-robot teaming (HRT). By examining the potential benefits, challenges, and risks, this research seeks to shed light on the responsible development and application of DTs in the context of Industry 5.0.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Harnessing-Digital-Twins-for-Human-Robot-Teaming-in-Industry-5.0-Exploring-the-Ethical-and-Philosophical-Implications.pdf"
}

Hua Minh Tuan, Even Falkenberg LangÅs, Muhammad Hamza Zafar and Filippo Sanfilippo. From Rigid to Hybrid/Soft Robots: Exploration of Ethical and Philosophical Aspects in Shifting from Caged Robots to Human-Robot Teaming. In Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-soft-robot-ethics,
	title = "From Rigid to Hybrid/Soft Robots: Exploration of Ethical and Philosophical Aspects in Shifting from Caged Robots to Human-Robot Teaming",
	author = "Tuan, Hua Minh and Lang{\aa}s, Even Falkenberg and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico",
	pages = "--",
	year = 2023,
	abstract = "This paper delves into the ethical, philosophical, and practical dimensions associated with the transition from caged robots to human-robot teaming (HRT). By exploring the evolving dynamics between humans and robots, this paper examines the ethical challenges, philosophical implications, and practical considerations that arise as collaboration and integration between humans and robots deepen. It emphasises the need for responsible design, implementation, and ethical frameworks to guide the development and deployment of human-robot teams. Particular focus is put into the ethical ramifications of choosing between rigid and soft actuators. The study underscores the significance of employing admittance and impedance control techniques to regulate interaction forces and compliance between humans and robots. By analysing the ethical implications of utilising soft actuators, the paper emphasises the potential advantages, such as enhanced safety and reduced risk of harm during close human-robot collaboration.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/From-Rigid-to-Hybrid-Soft-Robots-Exploration-of-Ethical-and-Philosophical-Aspects-in-Shifting-from-Caged-Robots-to-Human-Robot-Teaming.pdf"
}

Muhammad Hamza Zafar, Filippo Sanfilippo and Tomas Blazauskas. Harmony Unleashed: Exploring the Ethical and Philosophical aspects of Machine Learning in Human-Robot Collaboration for Industry 5.0. In Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-machine-learning-ethics,
	title = "Harmony Unleashed: Exploring the Ethical and Philosophical aspects of Machine Learning in Human-Robot Collaboration for Industry 5.0",
	author = "Zafar, Muhammad Hamza and Sanfilippo, Filippo and Blazauskas, Tomas",
	booktitle = "Proceeding of the 2023 IEEE Symposium Series on Computational Intelligence (SSCI 2023), Mexico City, Mexico",
	pages = "--",
	year = 2023,
	abstract = "As Industry 5.0 emerges by blending advanced technologies with human-centered approaches, the integration of machine learning (ML) in human-robot collaboration (HRC) becomes increasingly prominent. This paper explores the philosophy and ethics underlying the application of machine learning in Industry 5.0, specifically focusing on HRC. It examines the ethical considerations, philosophical implications, and potential challenges that arise in this evolving paradigm. The paper emphasises the need for a thoughtful and ethical approach to ensure the beneficial and responsible use of ML in Industry 5.0.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Harmony-Unleashed-Exploring-the-Ethical-and-Philosophical-aspects-of-Machine-Learning-in-Human-Robot-Collaboration-for-Industry-5.0.pdf"
}

Filip Górski, Dominik Rybarczyk, Radosław Wichniarek, Natalia Wierzbicka, Wiesław Kuczko, Magdalena Żukowska, Roman Regulski, Razvan Pacurar, Dan-Sorin Comsa, Diana-Irinel Baila, Martin Zelenay and Filippo Sanfilippo. Development and Testing of an Individualized Sensorised 3D Printed Upper Limb Bicycle Prosthesis for Adult Patients. Applied Sciences 13(23), 2023. URL, DOI BibTeX

@article{app132312918,
	author = "Górski, Filip and Rybarczyk, Dominik and Wichniarek, Radosław and Wierzbicka, Natalia and Kuczko, Wiesław and Żukowska, Magdalena and Regulski, Roman and Pacurar, Razvan and Comsa, Dan-Sorin and Baila, Diana-Irinel and Zelenay, Martin and Sanfilippo, Filippo",
	title = "Development and Testing of an Individualized Sensorised 3D Printed Upper Limb Bicycle Prosthesis for Adult Patients",
	journal = "Applied Sciences",
	volume = 13,
	year = 2023,
	number = 23,
	article-number = 12918,
	url = "https://www.mdpi.com/2076-3417/13/23/12918",
	issn = "2076-3417",
	abstract = "This paper presents the outcomes of investigations conducted on the development procedure of a personalized prosthetic device for an adult patient. The individualization is achieved through 3D scanning, followed by semi-automated design using the AutoMedPrint system, and low-cost fused deposition modelling (FDM) technology for 3D printing. The prosthesis is aimed for use during bicycle riding and other sport activities. During the conducted experiments outlined in this manuscript, the prosthesis is equipped with force and movement sensors. The purpose is to collect data on its functionality across different scenarios and dynamic activities, aiming to assess potential harm, refine the design, and serve as an initial step before activating the prosthesis end effector. This article describes the methodology in detail, including the process of designing, producing, and programming, as well as laboratory and field test results (including testing performed with and without a patient). Overall, the design and prototype are implemented successfully. A discussion about the need for particular improvements in both the mechanical and electrical areas is finally presented.",
	doi = "10.3390/app132312918"
}

Muhammad Hamza Zafar, Even Falkenberg Langås and Filippo Sanfilippo. Empowering human-robot interaction using sEMG sensor: Hybrid deep learning model for accurate hand gesture recognition. Results in Engineering 20:101639, 2023. URL PDF, DOI BibTeX

@article{ZAFAR2023101639,
	title = "Empowering human-robot interaction using sEMG sensor: Hybrid deep learning model for accurate hand gesture recognition",
	journal = "Results in Engineering",
	volume = 20,
	pages = 101639,
	year = 2023,
	issn = "2590-1230",
	doi = "https://doi.org/10.1016/j.rineng.2023.101639",
	url = "https://www.sciencedirect.com/science/article/pii/S2590123023007661",
	author = "Muhammad Hamza Zafar and Even {Falkenberg Langås} and Filippo Sanfilippo",
	keywords = "Surface EMG, Human-robot interaction, Deep learning, Discrete wavelet transform",
	abstract = "In this paper, a novel approach using a Henry Gas Solubility-based Stacked Convolutional Neural Network (HGS-SCNN) for hand gesture recognition using surface electromyography (sEMG) sensors is proposed. The stacked architecture of the CNN model helps to capture both low-level and high-level features, enabling effective representation learning. To begin, we generated a dataset comprising 600 samples of hand gestures. Next, we applied the Discrete Wavelet Transform (DWT) technique to extract features from the filtered sEMG signal. This step allowed us to capture both spatial and frequency information, enhancing the discriminative power of the extracted features. Extensive experiments are conducted to evaluate the performance of the proposed HGS-SCNN model. In addition, the obtained results are compared with state-of-the-art techniques, namely AOA-SCNN, GWO-SCNN, and WOA-SCNN. The comparative analysis demonstrates that the HGS-SCNN outperforms these existing methods, achieving an impressive accuracy of 99.3%. The experimental results validate the effectiveness of our proposed approach in accurately detecting hand gestures. The combination of DWT-based feature extraction and the HGS-SCNN model offers robust and reliable hand gesture recognition, thereby opening new possibilities for intuitive human-machine interaction and applications requiring gesture-based control.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Empowering-human-robot-interaction-using-sEMG-sensor-Hybrid-deep-learning-model-for-accurate-hand-gesture-recognition.pdf"
}

Aitzaz Ahmed Murtaza, Amina Saher, Hassan Mohyuddin, Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. Enhancing Cardiovascular Disease Prediction via Hybrid Deep Learning Architectures: A Step Towards Smart Healthcare. In Proceeding of the 2nd IEEE International Conference on Emerging Trends in Electrical, Control and Telecommunication Engineering (ETECTE'23), Lahore, Pakistan. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-smart-healthcare,
	title = "Enhancing Cardiovascular Disease Prediction via Hybrid Deep Learning Architectures: A Step Towards Smart Healthcare",
	author = "Murtaza, Aitzaz Ahmed and Saher, Amina and Mohyuddin, Hassan and Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 2nd IEEE International Conference on Emerging Trends in Electrical, Control and Telecommunication Engineering (ETECTE'23), Lahore, Pakistan",
	pages = "--",
	year = 2023,
	abstract = "Cardiovascular disease presents a serious and increasing global health challenge, making a substantial contribution to morbidity and mortality rates on a global scale. This research study presents a novel methodology for predicting Cardiovascular Diseases by employing a, recently developed, metaheuristic optimisation algorithm within a neural network framework. The Coati Optimisation Algorithm (COA) is employed in an artificial neural network (ANN) to enhance the predictive accuracy of outcomes related to Cardiovascular Diseases. The enhanced performance of the COA can be ascribed to its adept utilisation of both exploration and exploitation phenomena. This research employs publicly available datasets pertaining to heart and stroke disorders, integrating two datasets focused on heart disease and one dataset focused on stroke disease. A comparison analysis is undertaken between the proposed COA-ANN and existing approaches, namely Particle Swarm Optimizer based ANN (PSO-ANN), Grey Wolf Optimizer based ANN (GWO-ANN), and backpropagation based ANN (BP-ANN). The findings of the study indicate that the COA-ANN model exhibits the highest level of predictive accuracy. The COA- ANN outperformed the other three networks, namely GWO-ANN, PSO-ANN, and BP-ANN, with an average accuracy of 98.43%. As a result, the utilisation of the COA-ANN leads to an improvement in predictive accuracy for these datasets, with an increase of up to 2.64%. Additional assessment metrics, such as F1-Score, Precision, and Recall, provide more insight into the balanced performance of the COA-ANN architecture when applied to imbalanced class datasets. These results prove that the integration of nature-inspired algorithms with cardiovascular diseases (CVDs) is a promising direction for future research.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Enhancing-Cardiovascular-Disease-Prediction-via-Hybrid-Deep-Learning-Architectures-A-Step-Towards-Smart-Healthcare.pdf"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, Filippo Sanfilippo, Malik Naveed Akhter and Shahzaib Farooq Hadi. Early Mental Stress Detection Using Q-Learning Embedded Starling Murmuration Optimiser-based Deep Learning Model. IEEE Access 11():116860-116878, 2023. URL BibTeX

@article{moosavi2023early,
	title = "Early Mental Stress Detection Using Q-Learning Embedded Starling Murmuration Optimiser-based Deep Learning Model",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo and Akhter, Malik Naveed and Hadi, Shahzaib Farooq",
	journal = "IEEE Access",
	year = 2023,
	volume = 11,
	number = "",
	pages = "116860-116878",
	abstract = "Stress affects individual of all ages as a regular part of life, but excessive and chronic stress can lead to physical and mental health problems, decreased productivity, and reduced quality of life. By identifying stress at an early stage, individuals can take steps to manage it effectively and improve their overall well-being. Feature selection is a critical aspect of early stress detection because it helps identify the most relevant and informative features that can differentiate between stressed and non-stressed individuals. This paper firstly proposes a variance based feature selection technique that uses q-learning embedded Starling Murmuration Optimiser (QLESMO) to choose relevant features from a publicly available dataset in which stresses experienced by nurses working during the Covid’19 Pandemic is recorded using bio-signals and user surveys. Furthermore, a comparative study with other metaheuristic based feature selection techniques have been demonstrated. Next, to evaluate the efficacy of the proposed algorithm, 10 benchmark test functions have been used. The reduced feature subset is then classified through a 1D convolutional neural network (CNN) model (QLESMO-CNN) and is seen to perform well in terms of the evaluation metrics in comparison to other competitive algorithms. Finally, the proposed technique is compared with the State-of-the-Art methodologies present in literature. The experiments provide a strong basis to determine features that are most relevant for early mental stress classification using a hybrid model combining CNN, Reinforcement Learning and metaheuristic algorithms.",
	url = "https://doi.org/10.1109/access.2023.3326129"
}

Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Inverse Kinematic Modelling of a 3-DOF Robotic Manipulator using Hybrid Deep Learning Models. Procedia CIRP 120:213-218, 2023. URL, DOI BibTeX

@article{ZAFAR2023213,
	title = "Inverse Kinematic Modelling of a 3-DOF Robotic Manipulator using Hybrid Deep Learning Models",
	journal = "Procedia CIRP",
	volume = 120,
	pages = "213-218",
	year = 2023,
	note = "56th CIRP International Conference on Manufacturing Systems 2023",
	issn = "2212-8271",
	doi = "https://doi.org/10.1016/j.procir.2023.08.038",
	url = "https://www.sciencedirect.com/science/article/pii/S2212827123007096",
	author = "Muhammad Hamza Zafar and Syed Kumayl Raza Moosavi and Filippo Sanfilippo",
	keywords = "Deep Neural Network (DNN), Gannet Optimization Algorithm (GOA), Inverse Kinematic Modelling (IKM), Normalized Mean Square Error (NMSE)",
	abstract = "As the degrees of freedom (DOF) for a manipulator rise, so does the complexity of inverse kinematic modeling. This research provides an inverse kinematic model mapped with the aid of a Multilayer Deep Neural Network (DNN) trained using a unique meta-heuristic approach, namely the Gannet Optimization Algorithm (GOA), to decrease the computational weight and time lag for desired output transformation. The suggested design can automatically pick up on the kinematic characteristics of the manipulator. The sole observational basis for repeated learning is the link between input and output. Using the Robot Operating System (ROS), related simulations on a 3-DOF manipulator are performed. The simulation-generated dataset is split 65:35 for the purpose of training and testing the suggested model. Cost, time for the training data, mean relative error, normal mean square error, and mean absolute error for the test data are the metrics utilized for model validation. The efficacy and superiority of the suggested method are demonstrated by a comparison of the GOA-DNN model with the particle swarm optimization (PSO)-DNN and Grey Wolf Optimization (GWO)-DNN meta-heuristic DNN models."
}

Muhammad Hamza Zafar, Hassaan Bin Younus, Syed Kumayl Raza Moosavi, Majad Mansoor and Filippo Sanfilippo. Online PID Tuning of a 3-DoF Robotic Arm using a Metaheuristic Optimisation Algorithm: A Comparative Analysis. In Proceeding of the 29th International Conference on Information and Software Technologies (ICIST), Kaunas, Lithuania. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-online-pid-tuning,
	title = "Online PID Tuning of a 3-DoF Robotic Arm using a Metaheuristic Optimisation Algorithm: A Comparative Analysis",
	author = "Zafar, Muhammad Hamza and Younus, Hassaan Bin and Moosavi, Syed Kumayl Raza and Mansoor, Majad and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 29th International Conference on Information and Software Technologies (ICIST), Kaunas, Lithuania",
	pages = "--",
	year = 2023,
	abstract = "This paper presents a metaheuristic algorithm-based proportional–integral–derivative (PID) controller tuning method for a 3 degrees of freedom (DoF) robotic manipulator. In particular, the War Strategy Optimisation Algorithm (WSO) is applied as a metaheuristic algorithm for PID tuning of the manipulator, and the performance of the controller is compared with Particle Swarm Optimisation (PSO) and Grey Wolf Optimisation (GWO) algorithms. According to the simulation outcomes, the WSO algorithm exhibits superior performance compared to the other two algorithms with respect to settling time, overshoot, and steady-state error. The proposed technique provides an effective approach for enhancing the performance of robotic manipulators and can be extended to other applications that require optimal PID controller tuning.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Online-PID-Tuning-of-a-3-DoF-Robotic-Arm-Using-a-Metaheuristic-Optimisation-Algorithm-A-Comparative-Analysis.pdf"
}

Filip Górski, Remigiusz Łabudzki, Magdalena Zukowska, Filippo Sanfilippo, Morten Ottestad, Martin Zelenay, Diana-Irinel Baila and Razvan Pacurar. Experimental Evaluation of Extended Reality Technologies in the Development of Individualized Three-Dimensionally Printed Upper Limb Prostheses. Applied Sciences 13(14):8035, 2023. URL BibTeX

@article{gorski2023experimental,
	title = "Experimental Evaluation of Extended Reality Technologies in the Development of Individualized Three-Dimensionally Printed Upper Limb Prostheses",
	author = "G{\'o}rski, Filip and {\L}abudzki, Remigiusz and Zukowska, Magdalena and Sanfilippo, Filippo and Ottestad, Morten and Zelenay, Martin and Baila, Diana-Irinel and Pacurar, Razvan",
	journal = "Applied Sciences",
	volume = 13,
	number = 14,
	pages = 8035,
	year = 2023,
	publisher = "MDPI",
	abstract = "This paper presents results from experimental studies that assess the utilization of virtual, augmented, and mixed reality (VR, AR, MR) at different stages of developing personalized 3D printed upper limb prostheses for adult patients. The prostheses are designed automatically using the AutoMedPrint system, leveraging 3D scans as described in various prior publications. Various stages of development of the prosthesis are made as applications of different extended reality technologies. An assembly instruction is implemented as an immersive VR application, a configurator is designed as AR application and a configurator and try-on application is prepared and deployed in MR. The applications are tested by an international group of experts during a scheduled experiment. The experts then participate to surveys and comparatively evaluate the potential of all the XR technologies. The paper presents the development of these applications, provides a detailed account of the experimental process, including the rankings of XR technologies for different applications throughout the lifecycle of a prosthetic device.",
	url = "https://www.mdpi.com/2380668"
}

Hassan Mohyuddin, Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. A comprehensive framework for hand gesture recognition using hybrid-metaheuristic algorithms and deep learning models. Array 19:100317, 2023. URL BibTeX

@article{mohyuddin2023comprehensive,
	title = "A comprehensive framework for hand gesture recognition using hybrid-metaheuristic algorithms and deep learning models",
	author = "Mohyuddin, Hassan and Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	journal = "Array",
	volume = 19,
	pages = 100317,
	year = 2023,
	publisher = "Elsevier",
	abstract = "This paper presents a novel methodology that utilizes gesture recognition data, which are collected with a Leap Motion Controller (LMC), in tandem with the Spotted Hyena-based Chimp Optimization Algorithm (SSC) for feature selection and training of deep neural networks (DNNs). An expansive tabular database was created using the LMC for eight distinct gestures and the SSC algorithm was used for discerning and selecting salient features. This refined feature subset is then utilized in the subsequent training of a DNN model. A comprehensive comparative analysis is conducted to evaluate the performance of the SSC algorithm in comparison with established optimization techniques, such as Particle Swarm Optimization(PSO), Grey Wolf Optimizer(GWO), and Sine Cosine Algorithm(SCA), specifically in the context of feature selection. The empirical findings decisively establish the efficacy of the SSC algorithm, consistently achieving a high accuracy rate of 98% in the domain of gesture recognition tasks. The feature selection approach proposed emphasizes its intrinsic capacity to enhance not only the accuracy of gesture recognition systems and its wider suitability across diverse domains that require sophisticated feature extraction techniques.",
	url = "https://doi.org/10.1016/j.array.2023.100317"
}

Muhammad Hamza Zafar, Majad Mansoor, Mohamad Abou Houran, Noman Mujeeb Khan, Kamran Khan, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Hybrid deep learning model for efficient state of charge estimation of Li-ion batteries in electric vehicles. Energy 282:128317, 2023. URL BibTeX

@article{zafar2023hybrid,
	title = "Hybrid deep learning model for efficient state of charge estimation of Li-ion batteries in electric vehicles",
	author = "Zafar, Muhammad Hamza and Mansoor, Majad and Abou Houran, Mohamad and Khan, Noman Mujeeb and Khan, Kamran and Moosavi, Syed Kumayl Raza and Sanfilippo, Filippo",
	journal = "Energy",
	volume = 282,
	pages = 128317,
	year = 2023,
	publisher = "Elsevier",
	abstract = "State of charge (SoC) estimation is critical for the safe and efficient operation of electric vehicles (EVs). This work proposes a hybrid multi-layer deep neural network (HMDNN)-based approach for SoC estimation in EVs. This HMDNN uses Mountain Gazelle Optimizer (MGO) as a training algorithm for the deep neural network. Our method leverages the intrinsic relationship between the SoC and the voltage/current measurements of the EV battery to accurately estimate the SoC in real time. We evaluate our approach on a large dataset of real-world EV charging data and demonstrate its effectiveness in comparison to traditional SoC estimation methods. Four diverse Li-ion battery datasets of electric vehicles are employed which are the dynamic stress test (DST), Beijing dynamic stress test (BJDST), federal urban driving schedule (FUDS), and highway driving schedule (US06) with different temperatures of 0 C, 25 C, 45 C. The comparison is made with Mayfly Optimization Algorithm based DNN, Particle Swarm Optimization based DNN and Back-Propagation based DNN. The evaluation indices used are normalized mean square error (NMSE), root mean square error (RMSE), mean absolute error (MAE), and relative error (RE). The proposed algorithm achieves 0.1% NMSE and 0.3% RMSE on average on all datasets, which validates the effective performance of the proposed model. The results show that the proposed neural network-based approach can achieve higher accuracy and faster convergence than existing methods. This can enable more efficient EV operation and improved battery life.",
	url = "https://doi.org/10.1016/j.energy.2023.128317"
}

Muhammad Hamza Zafar, Syed Muhammad Salman Bukhari, Mohamad Abou Houran, Syed Kumayl Raza Moosavi, Majad Mansoor, Nedaa Al-Tawalbeh and Filippo Sanfilippo. Step towards secure and reliable smart grids in Industry 5.0: A federated learning assisted hybrid deep learning model for electricity theft detection using smart meters. Energy Reports 10:3001–3019, 2023. DOI BibTeX

@article{zafar2023step,
	title = "Step towards secure and reliable smart grids in Industry 5.0: A federated learning assisted hybrid deep learning model for electricity theft detection using smart meters",
	author = "Zafar, Muhammad Hamza and Bukhari, Syed Muhammad Salman and Abou Houran, Mohamad and Moosavi, Syed Kumayl Raza and Mansoor, Majad and Al-Tawalbeh, Nedaa and Sanfilippo, Filippo",
	journal = "Energy Reports",
	volume = 10,
	pages = "3001--3019",
	year = 2023,
	publisher = "Elsevier",
	abstract = "The integration of Smart Grid technology and conceptual Industry 5.0 has paved the way for advanced energy management systems that enhance efficiency and revolutionized the parallel integration of power sources in a sustainable manner. However, this digitization has opened a new stream of the threat and opportunities of electricity theft posing a significant challenge to the security and reliability of Smart Grid networks. In this paper, we propose a secure and reliable theft detection technique using deep federated learning (FL) mechanism. The technique leverages the collaborative power of FL to train a Convolutional Gated Recurrent Unit (ConvGRU) model on distributed data sources without compromising data privacy. The training deep learning model backbone consists of a ConvGRU model that combines convolutional and gated recurrent units to capture spatial and temporal patterns in electricity consumption data. An improvised preprocessing mechanism and hyperparameter tuning is done to facilitate FL mechanism. The halving randomized search algorithm is used for hyperparameters tuning of the ConvGRU model. The impact of hyperparameters involved in the ConvGRU model such as number of layers, filters, kernel size, activation function, pooling, GRU layers, hidden state dimension, learning rate, and the dropout rate is elaborated. The proposed technique achieves promising results, with high accuracy, precision, recall, and F1 score, demonstrating its efficacy in detecting electricity theft in Smart Grid networks. Comparative analysis with existing techniques reveal the superior performance of the deep FL-based ConvGRU model. The findings highlight the potential of this approach in enhancing the security and efficiency of Smart Grid systems while preserving data privacy.",
	doi = "https://doi.org/10.1016/j.egyr.2023.09.100"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, Seyedali Mirjalili and Filippo Sanfilippo. Improved Barnacles Movement Optimizer (IBMO) Algorithm for Engineering Design Problems. In Proceeding of the 22nd International Conference on Artificial Intelligence and Soft Computing (ICAISC 2023), Zakopane, Poland. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-barnacles,
	title = "Improved Barnacles Movement Optimizer (IBMO) Algorithm for Engineering Design Problems",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Mirjalili, Seyedali and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 22nd International Conference on Artificial Intelligence and Soft Computing (ICAISC 2023), Zakopane, Poland",
	pages = "--",
	year = 2023,
	abstract = "A better understanding of natural behavior modeling in math- ematical systems has enabled a new class of stochastic optimization al- gorithms that can estimate optimal solutions using reasonable compu- tational resources for problems where exact algorithms show poor per- formance. The position up-dating mechanism in various optimization algorithms utilizes similar chaotic random behavior which impedes the performance of the search for a globally optimum solution in monotonic nonlinear search space. In this work, an approach is proposed that tack- les these issues on an already established algorithm; Improved Barnacle Mating Optimization (IBMO) Algorithm, inspired by the movement and mating of Gooseneck Barnacles. The algorithm introduces the mimicry of the movement and mating behavior in nature to model an optimization process. Several benchmark functions and engineering case studies are employed to gauge the performance of the proposed optimization tech- nique. Results are compared with several meta-heuristics and conven- tional optimization algorithms. It is observed that the IBMO algorithm per-forms generally better and provides a huge potential for solving real- world problems.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Improved-Barnacles-Movement-Optimizer-IBMO-Algorithm-for-Engineering-Design-Problems.pdf"
}

Filippo Sanfilippo and Iñaki Rañó. Mimicking the Sense of Smell of Search and Rescue (SAR) Dogs: a Bio-inspired Steering Framework for Quadruped Robots. In Proceeding of 20th Annual Global Conference on Information Systems for Crisis Response and Management (ISCRAM 2023), Omaha, NE, USA. 2023, 892–901. PDF BibTeX

@inproceedings{sanfilippo-2023-smell-dog-robot,
	title = "Mimicking the Sense of Smell of Search and Rescue (SAR) Dogs: a Bio-inspired Steering Framework for Quadruped Robots",
	author = "Sanfilippo, Filippo and Ra{\~n}{\'o}, I{\~n}aki",
	booktitle = "Proceeding of 20th Annual Global Conference on Information Systems for Crisis Response and Management (ISCRAM 2023), Omaha, NE, USA",
	pages = "892--901",
	year = 2023,
	abstract = "Due to their sense of smell and ability to explore areas for missing people, dogs are valuable for search and rescue (SAR). Canines can discover humans under water, under snow, and even beneath crumbling structures because they can smell human scent. Building unmanned autonomous quadruped robots with canine agility is an attractive step to fully replicate the capabilities of dogs. Robots with legs are already capable of mimicking some of the physical traits of dogs, such as the capacity to traverse rough terrain. However, they would need to replicate also the level of sensory perception of a dog to successfully perform SAR operations. To achieve this, a navigation strategy that uses a direct sensor-motor coupling by following the principles of the Braitenberg vehicles is adopted in this work. This paper represents one of the first steps towards the connection of bio-inspired sensor-based steering mechanisms and bio-inspired locomotion for quadruped robots.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Mimicking-the-Sense-of-Smell-of-Search-and-Rescue-SAR-Dogs-a-Bio-inspired-Steering-Framework-for-Quadruped-Robots.pdf"
}

Muhammad Hamza Zafar, Noman Mujeeb Khan, Majad Mansoor and Filippo Sanfilippo. Optimal Tuning of PID Controller for Boost Converter using Meta-Heuristic Algorithm for Renewable Energy Applications. In Proceeding of the International Conference on Mechanical, Automotive and Mechatronics Engineering (ICMAME 2023), Dubai, United Arab Emirates. 2023, –. PDF BibTeX

@inproceedings{sanfilippo-2023-pid,
	title = "Optimal Tuning of PID Controller for Boost Converter using Meta-Heuristic Algorithm for Renewable Energy Applications",
	author = "Zafar, Muhammad Hamza and Khan, Noman Mujeeb and Mansoor, Majad and Sanfilippo, Filippo",
	booktitle = "Proceeding of the International Conference on Mechanical, Automotive and Mechatronics Engineering (ICMAME 2023), Dubai, United Arab Emirates",
	pages = "--",
	year = 2023,
	abstract = "The Dynamic Levy Flight Chimp optimisation (DLFC) method is used in this study to optimise the ProportionalIntegral-Derivative (PID) Controller for the Boost converter. As a possible application, the tuned PID controller is utilised to adjust voltages in the use of renewable power sources. The maximum power point tracking control approach based on machine learning (ML) is used to anticipate the reference voltages for the solar system based on the irradiance and the ambient temperature. The tuned PID controller uses this reference signal to regulate the maximum power point (MPP) voltages. To finetune the PID controller, comparisons are done with grey wolf optimiser (GWO), Harris hawk optimisation algorithms (HHO), and particle swarm optimisation (PSO) algorithms. The tuned PID controller has fewer oscillations and requires little tracking time to adapt to changing load and environment conditions. Additionally, statistical analysis, such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) between the reference voltage and the output voltage, is presented. Since the DLFC tuned PID controller performs better than HHO, GWO, and PSO in terms of RMSE and MAE, it may be a promising way for optimising PID controller tuning for boost converters in photovoltaic (PV) system applications.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Optimal-Tuning-of-PID-Controller-for-Boost-Converter-using-Meta-Heuristic-Algorithm-for-Renewable-Energy-Applications.pdf"
}

Hareesh Chitikena, Filippo Sanfilippo and Shugen Ma. Robotics in Search and Rescue (SAR) Operations: An Ethical and Design Perspective Framework for Response Phase. Applied Sciences 13(3), 2023. URL, DOI BibTeX

@article{Chitikena2023SAR,
	title = "Robotics in Search and Rescue (SAR) Operations: An Ethical and Design Perspective Framework for Response Phase",
	author = "Chitikena, Hareesh and Sanfilippo, Filippo and Ma, Shugen",
	journal = "Applied Sciences",
	volume = 13,
	number = 3,
	year = 2023,
	publisher = "MDPI",
	url = "https://www.mdpi.com/2076-3417/13/3/1800",
	issn = "2076-3417",
	abstract = "Every year, especially in urban areas, the population density rises quickly. The effects of catastrophes (i.e., war, earthquake, fire, tsunami) on people are therefore significant and grave. Assisting the impacted people will soon involve human-robot Search and Rescue (SAR) operations. Therefore, it is crucial to connect contemporary technology (i.e., robots and cognitive approaches) to SAR to save human lives. However, these operations also call for careful consideration of several factors, including safety, severity, and resources. Hence, ethical issues with technologies in SAR must be taken into consideration at the development stage. In this study, the most relevant ethical and design issues that arise when using robotic and cognitive technology in SAR are discussed with a focus on the response phase. Among the vast variety of SAR robots that are available nowadays, snake robots have shown huge potential; as they could be fitted with sensors and used for transporting tools to hazardous or confined areas that other robots and humans are unable to access. With this perspective, particular emphasis has been put on snake robotics in this study by considering ethical and design issues. This endeavour will contribute to providing a broader knowledge of ethical and technological factors that must be taken into account throughout the design and development of snake robots.",
	doi = "10.3390/app13031800"
}

Filippo Sanfilippo, Even Falkenberg LangÅs, Halima Bukhari and Stian Robstad. Pervasive and Connected Digital Twins for Edge Computing Enabled Industrial Applications. In Proceeding of the 56th Hawaii International Conference on System Sciences (HICSS 2023), Maui, Hawaii, United States of America. 2023, 6789–6798. URL BibTeX

@inproceedings{sanfilippo-2023-digital-twins,
	title = "Pervasive and Connected Digital Twins for Edge Computing Enabled Industrial Applications",
	author = "Sanfilippo, Filippo and Lang{\aa}s, Even Falkenberg and Bukhari, Halima and Robstad, Stian",
	booktitle = "Proceeding of the 56th Hawaii International Conference on System Sciences (HICSS 2023), Maui, Hawaii, United States of America",
	pages = "6789--6798",
	year = 2023,
	abstract = "A digital twin (DT) is a digital representation of a physical asset that serves as its counterpart - or twin. DTs differ from static, three-dimensional models in that they are continuously updated with data from numerous sources. In one continually changing world of pervasive computing, where computational and human intelligence are expanding everywhere, DTs can be regarded as the backbone for addressing the synergy of software, devices, movable objects, networks, and people. In this paper, we present a novel perspective for designing, prototyping and testing pervasive and connected DTs for edge computing enabled industrial applications. The provided paradigm allows for the creation of computational models for cloud computing as well as the transmission of data and computational intelligence through analytic platforms. A case study is presented to demonstrate the possibilities of the suggested framework. According to the outlined findings, the proposed architecture contributes to effective maintenance and management of infrastructures and facilities.",
	url = "https://hdl.handle.net/10125/103455"
}

Muhammad Kamran Khan, Muhammad Hamza Zafar, Saad Rashid, Majad Mansoor, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Improved Reptile Search Optimization Algorithm: Application on Regression and Classification Problems. Applied Sciences 13(2):945, 2023. URL BibTeX

@article{khan2023improved,
	title = "Improved Reptile Search Optimization Algorithm: Application on Regression and Classification Problems",
	author = "Khan, Muhammad Kamran and Zafar, Muhammad Hamza and Rashid, Saad and Mansoor, Majad and Moosavi, Syed Kumayl Raza and Sanfilippo, Filippo",
	journal = "Applied Sciences",
	volume = 13,
	number = 2,
	pages = 945,
	year = 2023,
	publisher = "MDPI",
	url = "https://www.mdpi.com/2076-3417/13/2/945"
}

Filippo Sanfilippo, Rein T Thorstensen, Ajit Jha, Zhiyu Jiang and Kjell G Robbersmyr. A Perspective Review on Digital Twins for Roads, Bridges, and Civil Infrastructures. In Proceeding of the 2nd IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Male, Maldives. 2022, –. URL PDF BibTeX

@inproceedings{sanfilippo2022twins,
	title = "A Perspective Review on Digital Twins for Roads, Bridges, and Civil Infrastructures",
	author = "Sanfilippo, Filippo and Thorstensen, Rein T. and Jha, Ajit and Jiang, Zhiyu and Robbersmyr, Kjell G.",
	booktitle = "Proceeding of the 2nd IEEE International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME), Male, Maldives",
	pages = "--",
	year = 2022,
	abstract = "A digital model that is the counterpart — or twin — of a physical asset is considered a digital twin. Digital twins are becoming one of the most important technology trends for transportation infrastructure because of their potential to increase asset reliability and performance. As they offer current information about the status of the road infrastructure and the risks connected to it, digital twins can be seen as the foundation of infrastructure decision-making. Digital twins provide civil engineers with the ability to visualise assets across their entire life cycle to track changes and to perform analysis that optimises asset performance. The aim of this paper is to present a novel perspective for designing, prototyping and testing digital twins of bridges and road infrastructure. The methodology used takes into account the potential for developing a digital twin for the road infrastructure, taking into account stratigraphic analysis, surface condition monitoring, and bridges structural analysis. We seek to stimulate global efforts towards the achievement of efficient maintenance and management of infrastructures and facilities.",
	url = "https://ieeexplore.ieee.org/document/9988693",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/A-Perspective-Review-on-Digital-Twins-for-Roads-Bridges-and-Civil-Infrastructures.pdf"
}

Filippo Sanfilippo, Martin Økter, Tine Eie and Morten Ottestad. An Open Framework for teaching Motion Control for Mechatronics Education. In Proceeding of the 7th IEEE International STEM Education Conference (iSTEM-Ed), Sukhothai, Thailand. 2022, 1–4. URL PDF BibTeX

@inproceedings{sanfilippo2022open,
	title = "An Open Framework for teaching Motion Control for Mechatronics Education",
	author = "Sanfilippo, Filippo and {\O}kter, Martin and Eie, Tine and Ottestad, Morten",
	booktitle = "Proceeding of the 7th IEEE International STEM Education Conference (iSTEM-Ed), Sukhothai, Thailand",
	pages = "1--4",
	year = 2022,
	abstract = "This paper proposes the introduction of a novel open prototyping framework that involves using low-cost commercial off-the-shelf (COTS) components and tools for the module of motion control, within mechatronics education. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. This is accomplished by integrating students in a series of well-organised theoretical lectures as well as hands-on, highly engaging labora-tory group projects. Surface learning parts and deep learning sections are combined frequently to encourage learners to grasp, make connections, and expand their knowledge. The structure of the course as well as the key topics are discussed. The proposed open framework, which consist of an elevator model, is presented in details.",
	url = "https://ieeexplore.ieee.org/document/9920788",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/An-Open-Framework-for-teaching-Motion-Control-for-Mechatronics-Education.pdf"
}

Filippo Sanfilippo, Martin Økter, Tine Eie and Morten Ottestad. Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model. Machines 10(10), 2022. URL, DOI BibTeX

@article{machines10100945,
	author = "Sanfilippo, Filippo and Økter, Martin and Eie, Tine and Ottestad, Morten",
	title = "Teaching Motion Control in Mechatronics Education Using an Open Framework Based on the Elevator Model",
	journal = "Machines",
	volume = 10,
	year = 2022,
	number = 10,
	article-number = 945,
	url = "https://www.mdpi.com/2075-1702/10/10/945",
	issn = "2075-1702",
	abstract = "Universities and other educational institutions may find it difficult to afford the cost of obtaining cutting-edge teaching resources. This study introduces the adoption of a novel open prototyping framework in the context of mechatronics education, employing low-cost commercial off-the-shelf (COTS) components and tools for the motion control module. The goal of this study is to propose a novel structure for the motion control module in the engineering mechatronics curriculum. The objective is to foster a new teaching method. From a methodology perspective, students are involved in a series of well-organised theoretical lectures as well as practical, very engaging group projects in the lab. To help students understand, draw connections, and broaden their knowledge, the methods of surface learning and deep learning are frequently mixed thoroughly. The structure of the course as well as the key topics are discussed. The proposed open framework, which consists of an elevator model, is presented in details. Students’ early evaluation indicates that the course organisation and subjects are successful and beneficial.",
	doi = "10.3390/machines10100945"
}

Svein Olav Nyberg, Kjell G Robbersmyr, Jan Andreas Holm and Filippo Sanfilippo. Tensile Experiments on Adhesion Between Aluminium Profiles and Glass. In Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021. 2022, 407–418. URL PDF BibTeX

@inproceedings{nyberg2022tensile,
	title = "Tensile Experiments on Adhesion Between Aluminium Profiles and Glass",
	author = "Nyberg, Svein Olav and Robbersmyr, Kjell G and Holm, Jan Andreas and Sanfilippo, Filippo",
	booktitle = "Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021",
	pages = "407--418",
	year = 2022,
	organization = "Springer",
	abstract = "In this work, the effects of the adhesion between aluminium profiles and glass are studied from a static tensile perspective. A series of stretch curves are analysed from their derivatives to find their points of float and maximum load bearing. The variable factors are glass type, and type of connection: i.e., edge adhesive, side (fugue) adhesive, and excessive fugue adhesive, for short named fugue-edge. The stretch data imply four quantities to analyse and compare: displacement and load respectively at float and at max load. The results are first compared factor group against factor group. With this tool, only a few significant conclusions may be found. The second comparison is by means of the more robust statistical tools of linear regression and analysis of variance (ANOVA), with conclusions about which factors are significant, and then about the size of the effect on the four variables under study. This forms the basis for a recommendations for how to obtain the strongest possible glass-frame system.",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-10525-8_32",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Tensile-Experiments-on-Adhesion-between-Aluminium-Profiles-and-Glass.pdf"
}

Kristian Muri KnausgÅrd, Siv Lene Gangenes Skar, Filippo Sanfilippo, Albert Buldenko, Henning Lindheim, Jakob Lunde, Eligijus Sukarevicius and Kjell G Robbersmyr. Branch-Manoeuvring Capable Pipe Cleaning Robot for Aquaponic Systems. In Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021. 2022, 107–118. URL PDF BibTeX

@inproceedings{knausgaard2022branch,
	title = "Branch-Manoeuvring Capable Pipe Cleaning Robot for Aquaponic Systems",
	author = "Knausg{\aa}rd, Kristian Muri and Skar, Siv Lene Gangenes and Sanfilippo, Filippo and Buldenko, Albert and Lindheim, Henning and Lunde, Jakob and Sukarevicius, Eligijus and Robbersmyr, Kjell G",
	booktitle = "Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021",
	pages = "107--118",
	year = 2022,
	organization = "Springer",
	abstract = "Aquaponic systems are engineered ecosystems combining aquaculture and plant production. Nutrient rich water is continuously circulating through the system from aquaculture tanks. A biofilter with nitrifying bacteria breaks down fish metabolism ammonia into nitrite and nitrate, which plants and makes the aquaculture wastewater into valued organic fertiliser for the plants, containing essential macro and micro elements. At the same time, the plants are cleaning the water by absorbing ammonia from the fish tanks before it reaches dangerous levels for the aquatic animals. In principle, the only external input is energy, mainly in the form of light and heat, but fish food is also commonly provided. Growing fish food is potentially feasible in a closed loop system, hence aquaponic systems can possibly be an important source of proteins and other important nutrition when, for example, colonising other planets in the future. Fully autonomous aquaponic systems are currently not available. This work aims at minimising manual labour related to cleaning pipes for water transport. The cleaning process must be friendly to both plants and aquatic animals. Hence, in this work, pure mechanical cleaning is adopted. A novel belt-driven continuum robot capable of travelling through small/medium diameter pipes and manoeuvring branches and bends, is designed and tested. The robot is modular and can be extended with different cleaning modules through an interface providing CAN-bus network and electric power. The flexible continuum modules of the robot are characterised. Experimental results demonstrate that the robot is able to travel through pipes with diameters varying from 50 mm to 75 mm, and also capable of handling T-branches of up to 90∘.",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-10525-8_9",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Branch-Manoeuvring-Capable-Pipe-Cleaning-Robot-for-Aquaponic-Systems.pdf"
}

Filippo Sanfilippo, Tomas Blažauskas, Martynas Girdži\=una, Airidas Janonis, Eligijus Kiudys and Gionata Salvietti. A multi-modal auditory-visual-tactile e-learning framework. In Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021. 2022, 119–131. URL PDF BibTeX

@inproceedings{sanfilippo2022multi,
	title = "A multi-modal auditory-visual-tactile e-learning framework",
	author = "Sanfilippo, Filippo and Bla{\v{z}}auskas, Tomas and Gird{\v{z}}i{\=u}na, Martynas and Janonis, Airidas and Kiudys, Eligijus and Salvietti, Gionata",
	booktitle = "Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021",
	pages = "119--131",
	year = 2022,
	organization = "Springer",
	abstract = "With a high number of countries closing learning institutions due to the restrictions in response to the COVID-19 pandemic, over 80% of the world’s students was not attending school. As a response to this challenge, many educational institutions are increasing their efforts to utilise various educational technologies and provide remote learning opportunities. One of the biggest drawbacks of the majority of these existing solutions is limited support for hands-on laboratory work and practical experiences. This is especially relevant to science, technology, engineering, and mathematics (STEM) departments, which must continuously develop their laboratories and pedagogical tools to provide their students with effective study plans. To facilitate a safe, digital access to laboratories, a novel haptic-enabled framework for hands-on e-Learning is introduced in this work. The framework enables a fully-immersive tactile, auditory, and visual experience. This is achieved by combining virtual reality (VR) tools, with a novel wearable haptic device, which is designed by augmenting a low-cost commercial off-the-shelf (COTS) controller with vibrotactile actuators. For this purpose, the Unity game engine and the Valve Knuckles EV3 controllers are adopted. To demonstrate the potential of the proposed framework, a human subject study is presented. Results suggest that the proposed haptic-enabled framework improves the student engagement and illusion of presence.",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-10525-8_10",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/A-Multi-modal-Auditory-Visual-Tactile-e-Learning-Framework.pdf"
}

Saishashank Balaji, Filippo Sanfilippo, Martin W Gerdes and Domenico Prattichizzo. A Perspective on Intervention Approaches for Children with Autism Spectrum Disorder. In Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021. 2022, 132–143. URL PDF BibTeX

@inproceedings{balaji2022perspective,
	title = "A Perspective on Intervention Approaches for Children with Autism Spectrum Disorder",
	author = "Balaji, Saishashank and Sanfilippo, Filippo and Gerdes, Martin W and Prattichizzo, Domenico",
	booktitle = "Proceeding of the International Conference on Intelligent Technologies and Applications, INTAP 2021, Grimstad, Norway, October 11–13, 2021",
	pages = "132--143",
	year = 2022,
	organization = "Springer",
	abstract = "Autism spectrum disorder (ASD) is a neurodevelopmental disorder that affects 1 in 160 children globally. Autism is characterised by abnormalities in communication, social interactions and behavioural challenges. Sensory processing difficulties affect two-thirds of children with autism. This causes anxiety and typically leads to repetitive behaviour referred to as problem behaviours. Stereotypy and aggression are some of the most frequently observed problem behaviours. Behavioural interventions may help manage symptoms and develop cognitive skills, thus promoting a child’s participation in social activities. A growing body of literature suggests that technological advancements in mobile health (mHealth) systems can be utilised to develop various intervention modalities. The central goal is to help children with ASD adapt to their surroundings by managing their problem behaviours. A promising possibility is to monitor physiological signals with wearable sensors to anticipate the onset of problem behaviour and provide intervention through wearable assistive devices. This paper presents a new perspective to manage problem behaviour and concept guidelines for a potential mHealth framework to deliver vibrotactile and thermal stimuli for sensory-based intervention.",
	url = "https://link.springer.com/chapter/10.1007/978-3-031-10525-8_11",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/A-Perspective-on-Intervention-Approaches-for-Children-with-Autism-Spectrum-Disorder.pdf"
}

Filippo Sanfilippo, Ole-Christoffer Granmo, Sule Yildirim-Yayilgan and Imran Sarwar Bajwa. Intelligent Technologies and Applications: 4th International Conference, INTAP 2021, Grimstad, Norway, October 11–13, 2021, Revised Selected Papers. Volume 1616, Springer Nature, 2022. URL BibTeX

@book{sanfilippo-2022-intap,
	author = "Sanfilippo, Filippo and Granmo, Ole-Christoffer and Yildirim-Yayilgan, Sule and Bajwa, Imran Sarwar",
	title = "Intelligent Technologies and Applications: 4th International Conference, INTAP 2021, Grimstad, Norway, October 11–13, 2021, Revised Selected Papers",
	publisher = "Springer Nature",
	year = 2022,
	volume = 1616,
	url = "https://link.springer.com/book/10.1007/978-3-031-10525-8"
}

Hua Minh Tuan, Filippo Sanfilippo and Nguyen Vinh Hao. A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm. Robotics 11(2), 2022. URL, DOI BibTeX

@article{robotics11020047,
	author = "Tuan, Hua Minh and Sanfilippo, Filippo and Hao, Nguyen Vinh",
	title = "A Novel Adaptive Sliding Mode Controller for a 2-DOF Elastic Robotic Arm",
	journal = "Robotics",
	volume = 11,
	year = 2022,
	number = 2,
	article-number = 47,
	url = "https://www.mdpi.com/2218-6581/11/2/47",
	issn = "2218-6581",
	abstract = "Collaborative robots (or cobots) are robots that are capable of safely operating in a shared environment or interacting with humans. In recent years, cobots have become increasingly common. Compliant actuators are critical in the design of cobots. In real applications, this type of actuation system may be able to reduce the amount of damage caused by an unanticipated collision. As a result, elastic joints are expected to outperform stiff joints in complex situations. In this work, the control of a 2-DOF robot arm with elastic actuators is addressed by proposing a two-loop adaptive controller. For the outer control loop, an adaptive sliding mode controller (ASMC) is adopted to deal with uncertainties and disturbance on the load side of the robot arm. For the inner loops, model reference adaptive controllers (MRAC) are utilised to handle the uncertainties on the motor side of the robot arm. To show the effectiveness of the proposed controller, extensive simulation experiments and a comparison with the conventional sliding mode controller (SMC) are carried out. As a result, the ASMC has a 50.35% lower average RMS error than the SMC controller, and a shorter settling time (5% criterion) (0.44 s compared to 2.11 s).",
	doi = "10.3390/robotics11020047"
}

Filippo Sanfilippo, Tomas Blazauskas, Gionata Salvietti, Isabel Ramos, Silviu Vert, Jaziar Radianti, Tim A Majchrzak and Daniel Oliveira. A Perspective Review on Integrating VR/AR with Haptics into STEM Education for Multi-Sensory Learning. Robotics 11(2), 2022. URL, DOI BibTeX

@article{robotics11020041,
	author = "Sanfilippo, Filippo and Blazauskas, Tomas and Salvietti, Gionata and Ramos, Isabel and Vert, Silviu and Radianti, Jaziar and Majchrzak, Tim A. and Oliveira, Daniel",
	title = "A Perspective Review on Integrating VR/AR with Haptics into STEM Education for Multi-Sensory Learning",
	journal = "Robotics",
	volume = 11,
	year = 2022,
	number = 2,
	article-number = 41,
	url = "https://www.mdpi.com/2218-6581/11/2/41",
	issn = "2218-6581",
	abstract = "As a result of several governments closing educational facilities in reaction to the COVID-19 pandemic in 2020, almost 80% of the world’s students were not in school for several weeks. Schools and universities are thus increasing their efforts to leverage educational resources and provide possibilities for remote learning. A variety of educational programs, platforms, and technologies are now accessible to support student learning; while these tools are important for society, they are primarily concerned with the dissemination of theoretical material. There is a lack of support for hands-on laboratory work and practical experience. This is particularly important for all disciplines related to science, technology, engineering, and mathematics (STEM), where labs and pedagogical assets must be continuously enhanced in order to provide effective study programs. In this study, we describe a unique perspective to achieving multi-sensory learning through the integration of virtual and augmented reality (VR/AR) with haptic wearables in STEM education. We address the implications of a novel viewpoint on established pedagogical notions. We want to encourage worldwide efforts to make fully immersive, open, and remote laboratory learning a reality.",
	doi = "10.3390/robotics11020041"
}

Askan Duivon, Pino Kirsch, Boris Mauboussin, Gabriel Mougard, Jakub Woszczyk and Filippo Sanfilippo. The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot. Robotics 11(2), 2022. URL, DOI BibTeX

@article{robotics11020042,
	author = "Duivon, Askan and Kirsch, Pino and Mauboussin, Boris and Mougard, Gabriel and Woszczyk, Jakub and Sanfilippo, Filippo",
	title = "The Redesigned Serpens, a Low-Cost, Highly Compliant Snake Robot",
	journal = "Robotics",
	volume = 11,
	year = 2022,
	number = 2,
	article-number = 42,
	url = "https://www.mdpi.com/2218-6581/11/2/42",
	issn = "2218-6581",
	abstract = "The term perception-driven obstacle-aided locomotion (POAL) was proposed to describe locomotion in which a snake robot leverages a sensory-perceptual system to exploit the surrounding operational environment and to identify walls, obstacles, or other structures as a means of propulsion. To attain POAL from a control standpoint, the accurate identification of push-points and reliable determination of feasible contact reaction forces are required. This is difficult to achieve with rigidly actuated robots because of the lack of compliance. As a possible solution to this challenge, our research group recently presented Serpens, a low-cost, open-source, and highly compliant multi-purpose modular snake robot with a series elastic actuator (SEA). In this paper, we propose a new prototyping iteration for our snake robot to achieve a more dependable design. The following three contributions are outlined in this work as a whole: the remodelling of the elastic joint with the addition of a damper element; a refreshed design for the screw-less assembly mechanism that can now withstand higher transverse forces; the re-design of the joint module with an improved reorganisation of the internal hardware components to facilitate heat dissipation and to accommodate a larger battery with easier access. The Robot Operating System (ROS) serves as the foundation for the software architecture. The possibility of applying machine learning approaches is considered. The results of preliminary simulations are provided.",
	doi = "10.3390/robotics11020042"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators. Robotics 11(2), 2022. URL, DOI BibTeX

@article{robotics11020043,
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	title = "Forward Kinematic Modelling with Radial Basis Function Neural Network Tuned with a Novel Meta-Heuristic Algorithm for Robotic Manipulators",
	journal = "Robotics",
	volume = 11,
	year = 2022,
	number = 2,
	article-number = 43,
	url = "https://www.mdpi.com/2218-6581/11/2/43",
	issn = "2218-6581",
	abstract = "The complexity of forward kinematic modelling increases with the increase in the degrees of freedom for a manipulator. To reduce the computational weight and time lag for desired output transformation, this paper proposes a forward kinematic model mapped with the help of the Radial Basis Function Neural Network (RBFNN) architecture tuned by a novel meta-heuristic algorithm, namely, the Cooperative Search Optimisation Algorithm (CSOA). The architecture presented is able to automatically learn the kinematic properties of the manipulator. Learning is accomplished iteratively based only on the observation of the input–output relationship. Related simulations are carried out on a 3-Degrees of Freedom (DOF) manipulator on the Robot Operating System (ROS). The dataset created from the simulation is divided 65–35 for training–testing of the proposed model. The metrics used for model validation include spread value, cost and runtime for the training dataset, and Mean Relative Error, Normal Mean Square Error, and Mean Absolute Error for the testing dataset. A comparative analysis of the CSOA-RBFNN model is performed with an artificial neural network, support vector regression model, and with with other meta-heuristic RBFNN models, i.e., PSO-RBFNN and GWO-RBFNN, that show the effectiveness and superiority of the proposed technique.",
	doi = "10.3390/robotics11020043"
}

Muhammad Hamza Zafar, Noman Mujeeb Khan, Majad Mansoor, Adeel Feroz Mirza, Syed Kumayl Raza Moosavi and Filippo Sanfilippo. Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems. Energy Conversion and Management 258:115564, 2022. URL, DOI BibTeX

@article{HAMZAZAFAR2022115564,
	title = "Adaptive ML-based technique for renewable energy system power forecasting in hybrid PV-Wind farms power conversion systems",
	journal = "Energy Conversion and Management",
	volume = 258,
	pages = 115564,
	year = 2022,
	issn = "0196-8904",
	doi = "https://doi.org/10.1016/j.enconman.2022.115564",
	url = "https://www.sciencedirect.com/science/article/pii/S0196890422003600",
	author = "Muhammad {Hamza Zafar} and Noman {Mujeeb Khan} and Majad Mansoor and Adeel {Feroz Mirza} and Syed {Kumayl Raza Moosavi} and Filippo Sanfilippo",
	keywords = "Power forecasting, Renewable energy resources (RES), Improved dynamic group based cooperative (IDGC)",
	abstract = "Large scale integration of renewable energy system with classical electrical power generation system requires a precise balance to maintain and optimize the supply–demand limitations in power grids operations. For this purpose, accurate forecasting is needed from wind energy conversion systems (WECS) and solar power plants (SPPs). This daunting task has limits with long-short term and precise term forecasting due to the highly random nature of environmental conditions. This paper offers a hybrid variational decomposition model (HVDM) as a revolutionary composite deep learning-based evolutionary technique for accurate power production forecasting in microgrid farms. The objective is to obtain precise short-term forecasting in five steps of development. An improvised dynamic group-based cooperative search (IDGC) mechanism with a IDGC-Radial Basis Function Neural Network (IDGC-RBFNN) is proposed for enhanced accurate short-term power forecasting. For this purpose, meteorological data with time series is utilized. SCADA data provide the values to the system. The improvisation has been made to the metaheuristic algorithm and an enhanced training mechanism is designed for the short term wind forecasting (STWF) problem. The results are compared with two different Neural Network topologies and three heuristic algorithms: particle swarm intelligence (PSO), IDGC, and dynamic group cooperation optimization (DGCO). The 24 h ahead are studied in the experimental simulations. The analysis is made using seasonal behavior for year-round performance analysis. The prediction accuracy achieved by the proposed hybrid model shows greater results. The comparison is made statistically with existing works and literature showing highly effective accuracy at a lower computational burden. Three seasonal results are compared graphically and statistically."
}

Filippo Sanfilippo. Combining Grasping with Adaptive Path Following and Locomotion for Modular Snake Robots. International Journal of Mechanical Engineering and Robotics Research 11(2):59–65, 2022. URL BibTeX

@article{sanfilippo2022snake-grasping,
	title = "Combining Grasping with Adaptive Path Following and Locomotion for Modular Snake Robots",
	author = "Sanfilippo, Filippo",
	journal = "International Journal of Mechanical Engineering and Robotics Research",
	volume = 11,
	number = 2,
	pages = "59--65",
	year = 2022,
	abstract = "In this paper, a framework architecture that combines grasping with adaptive locomotion for modular snake robots is presented. The proposed framework allows for simulating a snake robot model with locomotion and prehensile capabilities in a virtual environment. The simulated robot can be equipped with different sensors. Tactile perception can be achieved by using contact sensors to retrieve forces, torques, contact positions and contact normals. A camera can be attached to the snake robot head for visual perception purposes. To demonstrate the potential of the proposed framework, a case study is outlined concerning the execution of operations that combine locomotion and grasping. Related simulation results are presented.",
	url = "http://www.ijmerr.com/index.php?m=content&c=index&a=show&catid=206&id=1694"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar and Filippo Sanfilippo. A Review of the State-of-the-Art of Sensing and Actuation Technology for Robotic Grasping and Haptic Rendering. In Proceeding of the 5th International Conference on Information and Computer Technologies (ICICT), New York City (virtual), United States. 2022, –. URL PDF BibTeX

@inproceedings{sanfilippo-2022-grasping,
	title = "A Review of the State-of-the-Art of Sensing and Actuation Technology for Robotic Grasping and Haptic Rendering",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 5th International Conference on Information and Computer Technologies (ICICT), New York City (virtual), United States",
	pages = "--",
	year = 2022,
	abstract = "In this paper, a survey of the state of the art, challenges, and possibilities with sensing and actuation technology for robotic grasping and haptic rendering is presented. To this end, a survey and classification of robotic grippers and grasping methods is first outlined. Then, haptic rendering is surveyed by focusing on different challenges and approaches, such as rigid body haptic interaction, deformable/rigid haptic interaction, fluid haptic interaction, image/video based haptic interaction, and virtual reality (VR) based haptic interaction. Successively, the current sensing technology is reviewed by considering sensor development for robotic hands/grippers, such as tactile sensors, and visual sensors. Finally, the current actuation technology is addressed by considering soft robotic grippers, micro and nano grippers, multi-fingered grippers, and under actuated grippers. The main objective of this study is to boost worldwide efforts toward achieving the vast variety of applications that robotic grasping and haptics may give, as well as to provide an up-todate reference as a baseline for future research and development in this sector.",
	url = "https://ieeexplore.ieee.org/document/9845036",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/A-Review-of-the-State-of-the-Art-of-Sensing-and-Actuation-Technology-for-Robotic-Grasping-and-Haptic-Rendering.pdf"
}

Filippo Sanfilippo, Jesper Smith, Sylvain Bertrand and Tor Halvard Skarberg Svendsen. Mixed reality (MR) Enabled Proprio and Teleoperation of a Humanoid Robot for Paraplegic Patients. In Proceeding of the 5th International Conference on Information and Computer Technologies (ICICT), New York City (virtual), United States. 2022, –. URL PDF BibTeX

@inproceedings{sanfilippo-2022-mixed-reality-robot,
	title = "Mixed reality (MR) Enabled Proprio and Teleoperation of a Humanoid Robot for Paraplegic Patients",
	author = "Sanfilippo, Filippo and Smith, Jesper and Bertrand, Sylvain and Svendsen, Tor Halvard Skarberg",
	booktitle = "Proceeding of the 5th International Conference on Information and Computer Technologies (ICICT), New York City (virtual), United States",
	pages = "--",
	year = 2022,
	abstract = "Paraplegia is a disability caused by impairment in motor or sensory functions of the lower limbs. Most paraplegic subjects use mechanical or motorised wheelchairs for their movement, however, this may limit the capability of patients to independently perform common activities of daily living (ADL). In this paper, a novel mixed reality (MR) enabled proprio and teleoperation framework for a humanoid robot is presented. The framework can be operated by a paraplegic person by using inputs from an MR headset. The framework enables varied and unscripted manipulation tasks in a realistic environment, combining navigation, perception, manipulation, and grasping. The impaired operator can make use of a wide range of interaction methods and tools, from direct teleoperation of the robot’s full-body kinematics to performing grasping tasks or controlling the robot’s mobile base. The adopted humanoid robot is the EVEr3 Humanoid Research Robot from Halodi Robotics, while the Oculus Rift S is chosen as MR headset. To demonstrate the potential of the proposed framework, a human subject study is presented. In this study, a home/workplace environment is rendered with MR by combining physical shelves and everyday objects, such as goods to be grasped, with simulated elements, such as the robot avatar and the control interface. A paraplegic subject is involved in the study. Results suggest that the proposed MR-enabled system improves the patient engagement and illusion of presence.",
	url = "https://ieeexplore.ieee.org/document/9845013",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Mixed-Reality-MR-Enabled-Proprio-and-Teleoperation-of-a-Humanoid-Robot-for-Paraplegic-Patients.pdf"
}

Nurilla Avazov, Rym Hicheri, Muhammad Muaaz, Filippo Sanfilippo and Matthias Pätzold. A trajectory-driven 3D non-stationary mm-wave MIMO channel model for a single moving point scatterer. IEEE Access 9:115990–116001, 2021. URL BibTeX

@article{avazov2021trajectory,
	title = "A trajectory-driven 3D non-stationary mm-wave MIMO channel model for a single moving point scatterer",
	author = {Avazov, Nurilla and Hicheri, Rym and Muaaz, Muhammad and Sanfilippo, Filippo and P{\"a}tzold, Matthias},
	journal = "IEEE Access",
	volume = 9,
	pages = "115990--116001",
	year = 2021,
	publisher = "IEEE",
	abstract = "This paper proposes a new non-stationary three-dimensional (3D) channel model for a physical millimeter wave (mm-Wave) multiple-input multiple-output (MIMO) channel. This MIMO channel model is driven by the trajectory of a moving point scatterer, which allows us to investigate the impact of a single moving point scatterer on the propagation characteristics in an indoor environment. Starting from the time-variant (TV) channel transfer function, the temporal behavior of the proposed non-stationary channel model has been analyzed by studying the TV micro-Doppler characteristics and the TV mean Doppler shift. The proposed channel model has been validated by measurements performed in an indoor environment using a MIMO radar kit operating at 24 GHz. For the measurement campaign, we used a single swinging pendulum as a model for a moving point scatterer. The trajectory of the pendulum has been captured by an inertial measurement unit attached to the pendulum and by a motion capture camera system. The measured trajectories are fed into the proposed mm-Wave MIMO channel model. The results obtained for the micro-Doppler characteristics show an excellent agreement between the proposed MIMO channel model and real-world measured channels in the presence of a moving point scatterer. We believe that our model can serve as a basis for the development of novel non-stationary MIMO channel models capturing the effects caused by moving objects and people.",
	url = "https://ieeexplore.ieee.org/document/9514836"
}

Syed Kumayl Raza Moosavi, Muhammad Hamza Zafar, Malik Naveed Akhter, Shahzaib Farooq Hadi, Noman Mujeeb Khan and Filippo Sanfilippo. A Novel Artificial Neural Network (ANN) Using The Mayfly Algorithm for Classification. In Proceeding of the IEEE International Conference on Digital Futures and Transformative Technologies (ICoDT2), Islamabad, Pakistan. 2021, –. URL PDF BibTeX

@inproceedings{sanfilippo-2021-mayfly,
	title = "A Novel Artificial Neural Network (ANN) Using The Mayfly Algorithm for Classification",
	author = "Moosavi, Syed Kumayl Raza and Zafar, Muhammad Hamza and Akhter, Malik Naveed and Hadi, Shahzaib Farooq and Khan, Noman Mujeeb and Sanfilippo, Filippo",
	booktitle = "Proceeding of the IEEE International Conference on Digital Futures and Transformative Technologies (ICoDT2), Islamabad, Pakistan",
	pages = "--",
	year = 2021,
	abstract = "Training of Artificial Neural Networks (ANNs) have been improved over the years using meta heuristic algorithms that introduce randomness into the training method but they might be prone to falling into a local minima in a highdimensional space and have low convergence rate with the iterative process. To cater for the inefficiencies of training such an ANN, a novel neural network is presented in this paper using the bio-inspired algorithm of the movement and mating of the mayflies. The proposed Mayfly algorithm is explored as a means to update weights and biases of the neural network. As compared to previous meta heuristic algorithms, the proposed approach finds the global minima cost at far less number of iterations and with higher accuracy. The network proposed, which is named Mayfly Algorithm based Neural Network (MFANN) consists of an input layer, a single hidden layer of 10 neurons and an output layer. Two University of California Irvine (UCI) database sample datasets have been used as benchmark for this study, namely the Banknote Authentication (BA) and the Cryotherapy, for which the training accuracy achieved is 99.2350% and 96.6102%, whereas the Testing accuracy is 99.1247% and 90% respectively. Comparative study with grey wolf optimization neural network (GWONN) and particle swarm optimization neural network (PSONN) reveal that the proposed MFANN achieves 1-2% better accuracy with training dataset and 2% better accuracy with testing dataset.",
	url = "https://ieeexplore.ieee.org/document/9441473",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-novel-artificial-neural-network-ann-using-the-mayfly-algorithm-for-classification.pdf"
}

Filippo Sanfilippo and Kolbjørn Austreng. Sustainable Approach to Teaching Embedded Systems with Hands-On Project-Based Visible Learning. International Journal of Engineering Education 37(3):814–829, 2021. URL PDF BibTeX

@article{sanfilippo-embedded-systems,
	author = "Sanfilippo, Filippo and Austreng, Kolbj{\o}rn",
	title = "Sustainable Approach to Teaching Embedded Systems with Hands-On Project-Based Visible Learning",
	journal = "International Journal of Engineering Education",
	year = 2021,
	volume = 37,
	number = 3,
	pages = "814–829",
	abstract = "Although purchasing state-of-the-art teaching equipment may be financially demanding, substantial efforts are being made at the Norwegian University of Science and Technology (NTNU) in Trondheim to provide students with an enhanced hands-on embedded system design experience in a sustainable manner. In particular, an approach that consists of adopting low-cost commercial off-the-shelf (COTS) components and tools for learning purposes is proposed in this work. This strategy effectively combines both industry standard highly-reliable automation controllers, such as Programmable Logic Controller (PLC) technology, as well as novel microcontrollers (i.e., the micro:bit microcontroller based on the nRF51822 system-on-chip (SoC)) explicitly designed for use in embedded systems education. This contributes towards a hands-on sustainable learning experience based on the applicability of Visible Learning (VL). The objective of this paper is to propose a novel organisation of the embedded systems module for the engineering cybernetics education curriculum. The intended outcome is to promote a novel teaching approach. This is achieved by engaging students in both a series of organised theoretical lectures as well as practical and highly involving laboratory group projects. Surface learning sections and deep learning sections are thoroughly alternated to stimulate understanding, making relations, and extending the students’ knowledge. The course organisation and main topics, as well as result analysis of student surveys are discussed. The survey results and feedback from the reference group indicate that the course organisation and topics are effective and helpful for students.",
	url = "https://www.ijee.ie/latestissues/Vol37-3/21_ijee4070.pdf",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sustainable-approach-to-teaching-embedded-systems-with-hands-on-project-based-visible-learning.pdf"
}

Hua Minh Tuan, Filippo Sanfilippo and Nguyen Vinh Hao. Modelling and Control of a 2-DOF Robot Arm with Elastic Joints for Safe Human-Robot Interaction. Frontiers in Robotics and AI 8:223, 2021. URL BibTeX

@article{sanfilippo-sea-arm,
	author = "Tuan, Hua Minh and Sanfilippo, Filippo and Hao, Nguyen Vinh",
	title = "Modelling and Control of a 2-DOF Robot Arm with Elastic Joints for Safe Human-Robot Interaction",
	journal = "Frontiers in Robotics and AI",
	year = 2021,
	volume = 8,
	pages = 223,
	publisher = "Frontiers",
	abstract = "Collaborative robots (or cobots) are robots that can safely work together or interact with humans in a common space. They gradually become noticeable nowadays. Compliant actuators are very relevant for the design of cobots. This type of actuation scheme mitigates the damage caused by unexpected collision. Therefore, elastic joints are considered to outperform rigid joints when operating in a dynamic environment. However, most of the available elastic robots are relatively costly or difficult to construct. To give researchers a solution that is inexpensive, easily customisable, and fast to fabricate, a newly-designed low-cost, and open-source design of an elastic joint is presented in this work. Based on the newly design elastic joint, a highly-compliant multi-purpose 2-DOF robot arm for safe human-robot interaction is also introduced. The mechanical design of the robot and a position control algorithm are presented. The mechanical prototype is 3D-printed. The control algorithm is a two loops control scheme. In particular, the inner control loop is designed as a model reference adaptive controller (MRAC) to deal with uncertainties in the system parameters, while the outer control loop utilises a fuzzy proportional-integral controller to reduce the effect of external disturbances on the load. The control algorithm is first validated in simulation. Then the effectiveness of the controller is also proven by experiments on the mechanical prototype.",
	url = "https://www.frontiersin.org/article/10.3389/frobt.2021.679304"
}

Julie Madelen Madshaven, Tonje Fjeldstad Markseth, David Bye JomÅs, Ghislain Maurice Norbert Isabwe, Morten Ottestad, Frank Reichert and Filippo Sanfilippo. Investigating the User Experience of a Virtual Reality Rehabilitation Solution for a Biomechatronics Laboratory and Home Environment. Frontiers in Virtual Reality 2:54, 2021. URL BibTeX

@article{sanfilippo-biomechatronics,
	author = "Madshaven, Julie Madelen and Markseth, Tonje Fjeldstad and Jom{\aa}s, David Bye and Isabwe, Ghislain Maurice Norbert and Ottestad, Morten and Reichert, Frank and Sanfilippo, Filippo",
	title = "Investigating the User Experience of a Virtual Reality Rehabilitation Solution for a Biomechatronics Laboratory and Home Environment",
	journal = "Frontiers in Virtual Reality",
	year = 2021,
	volume = 2,
	pages = 54,
	publisher = "Frontiers",
	abstract = "Virtual reality (VR) technology is a promising tool in physical rehabilitation. Research indicates that VR-supported rehabilitation is beneficial for task-specific training, multi-sensory feedback, diversified rehabilitation tasks, and patient motivation. Our first goal was to create a biomechatronics laboratory with a VR setup for increasing immersion and a motion platform to provide realistic feedback to patients. The second goal was to investigate possibilities to replicate features of the biomechatronics laboratory in a home-based training system using commercially available components. The laboratory comprises of a motion platform with 6-degrees-of-freedom (Rexroth eMotion), fitted with a load cell integrated treadmill, and an Oculus Quest virtual reality headset. The load cells provide input for data collection, as well as VR motion control. The home-based rehabilitation system consists of a Nintendo Wii Balance Board and an Oculus Rift virtual reality headset. User studies in the laboratory and home environment used direct observation techniques and self-reported attitudinal research methods to assess the solution’s usability and user experience. The findings indicate that the proposed VR solution is feasible. Participants using the home-based system experienced more cybersickness and imbalance compared to those using the biomechatronics laboratory solution. Future studies will look at a setup that is safe for first patient studies, and exercises to improve diagnosis of patients and progress during rehabilitation.",
	url = "https://doi.org/10.3389/frvir.2021.645042"
}

Sule Yildirim Yayilgan, Imran Sarwar Bajwa and Filippo Sanfilippo. Intelligent Technologies and Applications: Third International Conference, INTAP 2020, Gjøvik, Norway, September 28–30, 2020, Revised Selected Papers. Volume 1382, Springer Nature, 2021. URL BibTeX

@book{sanfilippo-2021-intap,
	author = "Yildirim Yayilgan, Sule and Bajwa, Imran Sarwar and Sanfilippo, Filippo",
	title = "Intelligent Technologies and Applications: Third International Conference, INTAP 2020, Gjøvik, Norway, September 28–30, 2020, Revised Selected Papers",
	publisher = "Springer Nature",
	year = 2021,
	volume = 1382,
	abstract = "This book constitutes the refereed post-conference proceedings of the Third International Conference on Intelligent Technologies and Applications, INTAP 2020, held in Gjøvik, Norway, in September 2020. The 30 revised full papers and 4 revised short papers presented were carefully reviewed and selected from 117 submissions. The papers of this volume are organized in topical sections on image, video processing and analysis; security and IoT; health and AI; deep learning; biometrics; intelligent environments; intrusion and malware detection; and AIRLEAs.",
	url = "https://www.springer.com/gp/book/9783030717100"
}

Kristian G Hanssen, Aksel A Transeth, Filippo Sanfilippo, PÅl Liljebäck and Øyvind Stavdahl. Path Planning for Perception-Driven Obstacle-Aided Snake Robot Locomotion. In Proceeding of the IEEE 16th International Workshop on Advanced Motion Control (AMC), Kristiansand, Norway. 2020, 98–104. PDF BibTeX

@inproceedings{hanssen2020path,
	title = "Path Planning for Perception-Driven Obstacle-Aided Snake Robot Locomotion",
	author = {Hanssen, Kristian G and Transeth, Aksel A and Sanfilippo, Filippo and Liljeb{\"a}ck, P{\aa}l and Stavdahl, {\O}yvind},
	booktitle = "Proceeding of the IEEE 16th International Workshop on Advanced Motion Control (AMC), Kristiansand, Norway",
	pages = "98--104",
	year = 2020,
	abstract = "Development of snake robots have been motivated by the ability of snakes to move efficiently in unstructured and cluttered environments. A snake robot has the potential to utilise obstacles for generating locomotion, in contrast to wheeled robots which are unable to move efficiently in rough terrain. In this paper, we propose a local path planning algorithm for snake robots based on obstacle-aided locomotion (OAL). An essential feature in OAL is to determine suitable push-points in the environment that the snake robot can use for locomotion. The proposed method is based on a set of criteria for evaluating a path, and is a novel contribution of this paper. We focus on local path planning and formulate the problem as finding the best next push point and the trajectory towards it. The path is parameterised as a quadratic Bézier curve. The algorithm is implemented and tested with a simulator, employing decentralised joint controllers with references generated by a constant translation speed of the snake along the path. Careful design of the criteria allows us to use simple position and velocity controllers for the joints, circumventing the need for force control. However, the set of feasible paths will be restricted by this approach. The proposed criteria can also be used in a global path planning algorithm; the local focus is due to one of the key use cases of snake robots: operating in unstructured and unknown environments.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Path_Planning_for_Perception_Driven_Obstacle_Aided_Snake_Robot_Locomotion.pdf"
}

Steven Bos, Henning Gundersen and Filippo Sanfilippo. uMemristorToolbox: Open Source Framework to Control Memristors in Unity for Ternary Applications. In Proceeding of the IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL), Miyazaki, Japan. 2020. PDF BibTeX

@inproceedings{bos2020umemristortoolbox,
	title = "uMemristorToolbox: Open Source Framework to Control Memristors in Unity for Ternary Applications",
	author = "Bos, Steven and Gundersen, Henning and Sanfilippo, Filippo",
	booktitle = "Proceeding of the IEEE 50th International Symposium on Multiple-Valued Logic (ISMVL), Miyazaki, Japan",
	year = 2020,
	abstract = "This paper presents uMemristorToolbox, a novel open source framework that reads and writes non-volatile ternary states to memristors. The Unity (C#) framework is a port of the open source Java project Memristor-Discovery and adds a closed-loop ternary memory controller to enable both PC and real-time embedded ternary applications. We validate the closed-loop ternary memory controller in an embedded system case study with 16 M+SDC Tungsten dopant memristors. We measure an average switching speed of 3 Hz, worst case energy usage of 1 μW per switch, 0.03% random write error and no decay in (non-volatile) state retention after 15 minutes. We conclude with observations and open questions when working with memristors for ternary applications.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/umemristortoolbox-open-source-framework-to-control-memristors-in-unity-for-ternary-applications.pdf"
}

Filippo Sanfilippo, Min Tang and Sam Steyaert. The Aquatic Surface Robot (AnSweR), a lightweight, low cost, multipurpose unmanned research vessel. In Proceeding of the 3rd International Conference on Intelligent Technologies and Applications (INTAP), Gjøvik, Norway. 2020. PDF BibTeX

@inproceedings{sanfilippo-2020-answer-robots,
	title = "The Aquatic Surface Robot ({AnSweR}), a lightweight, low cost, multipurpose unmanned research vessel",
	author = "Sanfilippo, Filippo and Tang, Min and Steyaert, Sam",
	booktitle = "Proceeding of the 3rd International Conference on Intelligent Technologies and Applications (INTAP), Gj{\o}vik, Norway",
	year = 2020,
	abstract = "Even though a few examples of aquatic surface robots exist, they are generally expensive, relatively large and heavy and tailored to custom-made hardware/software components that are not openly available to a broad public. In this work, the Aquatic Surface Robot (AnSweR), a newly-designed, lightweight, low cost, open-source, multipurpose unmanned research vessel is presented. The AnSweR features a lightweight and compact design that makes it fit in a backpack. Low-noise operation (in and above the surface) is achieved with a propulsion system based on two water-jets. Only affordable commercial-off-the-shelf (COTS) components are adopted. The primary goal of the AnSweR is to map underwater landscapes and to collect bathymetry data in lakes, rivers, and coastal ecosystems. A modular hardware and software architecture is adopted. This architecture allows the AnSweR to be equipped with a customisable add-on set of sensors and actuators to enable a variety of research activities, such as measuring environmental variables (e.g., salinity, oxygen, temperature) and sampling operations (e.g., sediment, vegetation, microplastics). The software architecture is based on the Robot Operating System (ROS). This paper describes the design of AnSweR as the main scientific contribution and presents preliminary simulation and experimental results which illustrate its potential.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/the-aquatic-surface-robot-answer-a-lightweight-low-cost-multipurpose-unmanned-research-vessel.pdf"
}

Filippo Sanfilippo, Min Tang and Sam Steyaert. Aquatic Surface Robots: the State of the Art, Challenges and Possibilities. In Proceeding of the 1st IEEE International Conference on Human-Machine Systems (ICHMS), Roma, Italy. 2020. PDF BibTeX

@inproceedings{sanfilippo-2020-aquatic-surface-robots,
	title = "Aquatic Surface Robots: the State of the Art, Challenges and Possibilities",
	author = "Sanfilippo, Filippo and Tang, Min and Steyaert, Sam",
	booktitle = "Proceeding of the 1st IEEE International Conference on Human-Machine Systems (ICHMS), Roma, Italy",
	year = 2020,
	abstract = "In this paper, a survey of the state of the art, challenges, and possibilities for aquatic surface robots is presented. To this end, a survey and classification of aquatic surface robots is first outlined. Then, different levels of autonomy are identified for this typology of robots and categorised into environmental complexity, mission complexity, and external system independence. From this perspective, a step-wise approach is adopted on how to increment aquatic surface robots abilities within guidance, navigation, and control in order to target the different levels of autonomy. Possibilities and challenges for designing aquatic surface robots as carriers for conducting research activities are discussed. The main goal of this paper is to further increase global efforts to realise the wide range of possible applications offered by aquatic surface robots and to provide an up-to-date reference as a benchmark for new research and development in this field.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/aquatic-surface robots-the-state-of-the-art-challenges-and-possibilities.pdf"
}

Mathias Arbo, Ivar Eriksen, Filippo Sanfilippo and Jan Tommy Gravdahl. Comparison of KVP and RSI for Controlling KUKA Robots Over ROS. In Proceeding of the 21st IFAC World Congress, Berlin, Germany. 2020. PDF BibTeX

@inproceedings{sanfilippo-2020-kuka-ros,
	title = "Comparison of KVP and RSI for Controlling KUKA Robots Over ROS",
	author = "Arbo, Mathias and Eriksen, Ivar and Sanfilippo, Filippo and Gravdahl, Jan Tommy",
	booktitle = "Proceeding of the 21st IFAC World Congress, Berlin, Germany",
	year = 2020,
	abstract = "In this work, an open-source ROS interface based on KUKAVARPROXY for control of KUKA robots is compared to the commercial closed-source Robot Sensor Interface available from KUKA. This comparison looks at the difference in how these two approaches communicate with the KUKA robot controller, the response time and tracking delay one can expect with the different interfaces, and the difference in use cases for the two interfaces. The investigations showed that the KR16 with KRC2 has a 50 ms response time, and RSI has a 120 ms tracking delay, with negligible delay caused by the ROS communication stack. The results highlight that the commercial inferface is more reliable for feedback control tasks, but the proposed interface gives read and write access to variables on the controller during execution, and can be used for simple motion and tooling control.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/comparison-of-kvp-and-rsi-for-controlling-kuka-robots-over-ros.pdf"
}

Filippo Sanfilippo and Claudio Pacchierotti. A Low-Cost Multi-Modal Auditory-Visual-Tactile Framework for Remote Touch. In Proceeding of the 3rd IEEE International Conference on Information and Computer Technologies (ICICT), Silicon Valley, San Jose, United States. 2020, 213–218. PDF BibTeX

@inproceedings{sanfilippo-2020-haptic-gloves,
	title = "A Low-Cost Multi-Modal Auditory-Visual-Tactile Framework for Remote Touch",
	author = "Sanfilippo, Filippo and Pacchierotti, Claudio",
	booktitle = "Proceeding of the 3rd IEEE International Conference on Information and Computer Technologies (ICICT), Silicon Valley, San Jose, United States",
	pages = "213--218",
	year = 2020,
	abstract = "Haptic technology for human augmentation provides gains in ability for different applications, whether the aim is to enhance “disabilities” to “abilities”, or “abilities” to “super-abilities”. Commercially-available devices are generally expensive and tailored to specific applications and hardware. To give researchers a haptic feedback system that is economical, customisable, and fast to fabricate, our group developed a low-cost immersive haptic, audio, and visual experience built by using off-the-shelf (COTS) components. It is composed of a vibrotactile glove, a Leap Motion sensor, and an head-mounted display, integrated together to provide compelling immersive sensations. This paper proposes a higher technology readiness level (TRL) for the system to make it modular and reliable. To demonstrate its potential, we present two human subject studies in Virtual Reality. They evaluate the capability of the system in providing (i) guidance during simulated drone operations, and (ii) contact haptic feedback during virtual objects interaction. Results prove that the proposed haptic-enabled framework improves the performance and illusion of presence.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-low-cost-multi-modal-auditory-visual-tactile-framework-for-remote-touch.pdf"
}

Filippo Sanfilippo, Tuan Hua and Steven Bos. A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators. In Proceeding of the 53rd Hawaii International Conference on System Sciences (HICSS 2020), Maui, Hawaii, United States of America. 2020, 881–890. URL BibTeX

@inproceedings{sanfilippo-2020-reinforcement-learning-algorithm-snake,
	title = "A comparison between a two feedback control loop and a reinforcement learning algorithm for compliant low-cost series elastic actuators",
	author = "Sanfilippo, Filippo and Hua, Tuan and Bos, Steven",
	booktitle = "Proceeding of the 53rd Hawaii International Conference on System Sciences (HICSS 2020), Maui, Hawaii, United States of America",
	pages = "881--890",
	year = 2020,
	abstract = "Highly-compliant elastic actuators have become progressively prominent over the last years for a variety of robotic applications. With remarkable shock tolerance, elastic actuators are appropriate for robots operating in unstructured environments. In accordance with this trend, a novel elastic actuator was recently designed by our research group for Serpens, a low-cost, open-source and highly-compliant multi-purpose modular snake robot. To control the newly designed elastic actuators of Serpens, a two-feedback loops position control algorithm was proposed. The inner controller loop is implemented as a model reference adaptive controller (MRAC), while the outer control loop adopts a fuzzy proportional-integral controller (FPIC). The performance of the presented control scheme was demonstrated through simulations. However, the efficiency of the proposed controller is dependent on the initial values of the parameters of the MRAC controller as well as on the effort required for a human to manually construct fuzzy rules. An alternative solution to the problem might consist of using methods that do not assume a priori knowledge: a solution that derives its properties from a machine learning procedure. In this way, the controller would be able to automatically learn the properties of the elastic actuator to be controlled. In this work, a novel controller for the proposed elastic actuator is presented based on the use of an artificial neural network (ANN) that is trained with reinforcement learning. The newly designed control algorithm is extensively compared with the former approach. Simulation results are presented for both methods. The authors seek to achieve a fair, non-biased, risk-aware and trustworthy comparison.",
	url = "http://hdl.handle.net/10125/63849"
}

Hua Tuan Minh, Filippo Sanfilippo and Erlend Helgerud. A robust two-feedback loops position control algorithm for compliant low-cost series elastic actuators. In Proceeding of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy. 2019, 2384–2390. PDF BibTeX

@inproceedings{sanfilippo-2019-series-elastic-actuators,
	title = "A robust two-feedback loops position control algorithm for compliant low-cost series elastic actuators",
	author = "Tuan Minh, Hua and Sanfilippo, Filippo and Helgerud, Erlend",
	booktitle = "Proceeding of the IEEE International Conference on Systems, Man, and Cybernetics (SMC), Bari, Italy",
	pages = "2384--2390",
	year = 2019,
	abstract = "Elastic joints are considered to outperform rigid joints in terms of peak dynamics, collision tolerance, robustness, and energy efficiency. Therefore, intrinsically elastic joints have become progressively prominent over the last years for a variety of robotic applications. In this article, a two-feedback loops position control algorithm is proposed for an elastic actuator to deal with the influence from external disturbances. The considered elastic actuator was recently designed by our research group for Serpens, a low-cost, open-source and highly-compliant multi-purpose modular snake robot. In particular, the inner controller loop is implemented as a model reference adaptive controller (MRAC) to cope with uncertainties in the system parameters, while the outer control loop adopts a fuzzy proportional-integral controller (FPIC) to reduce the effect of external disturbances on the load. The advantage of combining the FPIC and the MRAC controllers is the possibility of achieving independence with respect to imprecise system parameters. A mathematical model of the considered elastic actuator is also presented to validate the proposed controller through simulations. The operability of the presented control scheme is demonstrated. In closed-loop the load swing is rapidly confined and eliminated thereafter.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-robust-two-feedback-loops-position-control-algorithm-for-compliant-low-cost-series-elastic-actuators.pdf"
}

Thong Ho-Sy, Filippo Sanfilippo and Vinh Truong-Quang. A Hybrid Algorithm Based on WiFi for Robust and Effective Indoor Positioning. In Proceeding of the 19th IEEE International Symposium on Communications and Information Technologies (ISCIT), Ho Chi Minh City, Vietnam. 2019, 416–421. PDF BibTeX

@inproceedings{sanfilippo-2019-wifi-indoor-positioning,
	title = "A Hybrid Algorithm Based on WiFi for Robust and Effective Indoor Positioning",
	author = "Ho-Sy, Thong and Sanfilippo, Filippo and Truong-Quang, Vinh",
	booktitle = "Proceeding of the 19th IEEE International Symposium on Communications and Information Technologies (ISCIT), Ho Chi Minh City, Vietnam",
	pages = "416--421",
	year = 2019,
	abstract = "Indoor positioning based on the Wireless Fidelity (WiFi) protocol and the Pedestrian Dead Reckoning (PDR) approach is widely exploited because of the existing WiFi infrastructure in buildings and the advancement of built-in smartphone sensors. In this work, a hybrid algorithm that combines WiFi fingerprinting and PDR to both exploit their advantages as well as limiting the impact of their disadvantages is proposed. Specifically, to build a probability map from noisy Received Signal Strength (RSS), a Gaussian Process (GP) regression is deployed to estimate and construct the RSS fingerprints with incomplete data. Mean and variance of generated points are used to estimate WiFi fingerprinting position by K-nearest weights from the probability of visible RSS measurements of the online phase. In addition, a particle filter is applied to fuse PDR and WiFi fingerprinting by using the information from RSS, inertial sensors and features of indoor maps. To demonstrate the potential of the proposed framework, two case studies are considered. In the first case, a comparison is made between GP regression with K-Nearest Neighbours (KNN) method to show the improvement with a sparse input data set. In the second case, the proposed framework is compared to both the fingerprinting approach as well as the PDR algorithm. The results show significant improvements from our proposed framework. The average positioning accuracy of our proposed system can be lower than 1.2 m, which was reduced by 48\% and 70\% compared with the WiFi fingerprinting and the PDR method, respectively.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-hybrid-algorithm-based-on-wifi-for-robust-and-effective-indoor-positioning.pdf"
}

Lina J Wali and Filippo Sanfilippo. A Review of the State-of-the-Art of Assistive Technology for People with ASD in the Workplace and in Everyday Life. In Digital Transformation for a Sustainable Society in the 21st Century. 2019, 520–532. PDF BibTeX

@inproceedings{sanfilippo-2019-state-of-the-art-assistive-technology-asd,
	title = "A Review of the State-of-the-Art of Assistive Technology for People with ASD in the Workplace and in Everyday Life",
	author = "Wali, Lina J. and Sanfilippo, Filippo",
	booktitle = "Digital Transformation for a Sustainable Society in the 21st Century",
	pages = "520--532",
	year = 2019,
	publisher = "Springer International Publishing",
	abstract = "Autism, also known as autism spectrum disorder (ASD), is an incurable brain-based disorder that refers to a wide range of complex neurodevelopment disorders characterised by marked difficulties in communication and social skills, repetitive behaviour, highly focused interests and sensory sensitivity. Autism can present challenges for affected people at the work environment and in everyday life. The barrier for individuals with ASD increases further with changing environmental situations. Individuals with ASD have limited abilities to isolate their Five senses and often experience over- or under-sensitivity to sounds, touch, tastes, smells, light, colours or temperatures. In this perspective, individuals with autism may experience extraordinary challenges during a regular day for most people, especially in non-conductive crowded environments like workplaces.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-review-of-the-state-of-the-art-of-assistive-technology-for-people-with-asd-in-the-workplace-and-in-everyday-life.pdf"
}

Filippo Sanfilippo, Erlend Helgerud, Per Anders Stadheim and Sondre Lieblein Aronsen. Serpens, a low-cost snake robot with series elastic torque-controlled actuators and a screw-less assembly mechanism. In Proceeding of the 5th IEEE International Conference on Control, Automation and Robotics (ICCAR 2019), Beijing, China. 2019, 133–139. PDF BibTeX

@inproceedings{sanfilippo-2019-serpens-conference,
	title = "Serpens, a low-cost snake robot with series elastic torque-controlled actuators and a screw-less assembly mechanism",
	author = "Sanfilippo, Filippo and Helgerud, Erlend and Stadheim, Per Anders and Aronsen, Sondre Lieblein",
	booktitle = "Proceeding of the 5th IEEE International Conference on Control, Automation and Robotics (ICCAR 2019), Beijing, China",
	pages = "133--139",
	year = 2019,
	abstract = "Even though a few examples of elastic snake robots exist, they are generally expensive and tailored to custom-made hardware/software components that are not openly available off-the-shelf. In this work, Serpens, a newly- designed low-cost, open-source and highly-compliant multi- purpose modular snake robot with series elastic actuator (SEA) is presented. Serpens features precision torque control and stereoscopic vision. Only low-cost commercial-off-the-shelf (COTS) components are adopted. The robot modules can be 3D-printed by using Fused Deposition Modelling (FDM) manufacturing technology, thus making the rapid-prototyping process very economical and fast. A screw-less assembly mechanism allows for connecting the modules and reconfigure the robot in a very reliable and robust manner. By combining the rapid-prototyping approach with the modular concept, different configurations can be achieved. By using a low-cost sensing approach, functions for torque sensing at the joint level, sensitive collision detection and joint compliant control are possible. The concept of modularity is also applied to the system architecture on both the software and hardware sides. Each module is independent, being controlled by a self-reliant controller board. The software architecture is based on the Robot Operating System (ROS). This paper describes the design of Serpens and presents preliminary simulation and experimental results which illustrate its potential.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/serpens-a-low-cost-snake-robot-with-series-elastic-torque-controlled-actuators.pdf"
}

Filippo Sanfilippo, Erlend Helgerud, Per Anders Stadheim and Sondre Lieblein Aronsen. Serpens: A Highly Compliant Low-Cost ROS-Based Snake Robot with Series Elastic Actuators, Stereoscopic Vision and a Screw-Less Assembly Mechanism. Applied Sciences 9(3)(396), January 2019. URL, DOI BibTeX

@article{sanfilippo2019serpens,
	author = "Sanfilippo, Filippo and Helgerud, Erlend and Stadheim, Per Anders and Aronsen, Sondre Lieblein",
	title = "Serpens: A Highly Compliant Low-Cost ROS-Based Snake Robot with Series Elastic Actuators, Stereoscopic Vision and a Screw-Less Assembly Mechanism",
	journal = "Applied Sciences",
	year = 2019,
	month = "January",
	volume = "9(3)",
	number = 396,
	url = "http://www.mdpi.com/2076-3417/9/3/396",
	issn = "2076-3417",
	abstract = "Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion is defined as perception-driven obstacle-aided locomotion (POAL). From a control point of view, achieving POAL with traditional rigidly-actuated robots is challenging because of the complex interaction between the snake robot and the immediate environment. To simplify the control complexity, compliant motion and fine torque control on each joint is essential. Accordingly, intrinsically elastic joints have become progressively prominent over the last years for a variety robotic applications. Commonly, elastic joints are considered to outperform rigid actuation in terms of peak dynamics, robustness, and energy efficiency. Even though a few examples of elastic snake robots exist, they are generally expensive to manufacture and tailored to custom-made hardware/software components that are not openly available off-the-shelf. In this work, Serpens, a newly-designed low-cost, open-source and highly-compliant multi-purpose modular snake robot with series elastic actuator (SEA) is presented. Serpens features precision torque control and stereoscopic vision. Only low-cost commercial-off-the-shelf (COTS) components are adopted. The robot modules can be 3D-printed by using Fused Deposition Modelling (FDM) manufacturing technology, thus making the rapid-prototyping process very economical and fast. A screw-less assembly mechanism allows for connecting the modules and reconfigure the robot in a very reliable and robust manner. The concept of modularity is also applied to the system architecture on both the software and hardware sides. Each module is independent, being controlled by a self-reliant controller board. The software architecture is based on the Robot Operating System (ROS). This paper describes the design of Serpens and presents preliminary simulation and experimental results, which illustrate its performance.",
	doi = "10.3390/app9030396"
}

Filippo Sanfilippo and Kiran Raja. A Multi-Sensor System for Enhancing Situational Awareness and Stress Management for People with ASD in the Workplace and in Everyday Life. In Proceeding of the 52nd Hawaii International Conference on System Sciences (HICSS 2019), Maui, Hawaii, United States of America. 2019, 4079–4086. URL BibTeX

@inproceedings{sanfilippo-2019-asd-autism,
	title = "A Multi-Sensor System for Enhancing Situational Awareness and Stress Management for People with ASD in the Workplace and in Everyday Life",
	author = "Sanfilippo, Filippo and Raja, Kiran",
	booktitle = "Proceeding of the 52nd Hawaii International Conference on System Sciences (HICSS 2019), Maui, Hawaii, United States of America",
	pages = "4079--4086",
	year = 2019,
	abstract = "Autism spectrum disorders (ASD) present challenges for affected people at work and in everyday life. The barrier increases further with changing environmental situations. Deviations in factors like lighting or sound may lead to increased stress. The intervention plans to instil positive behaviour support (PBS) suggest that a customised environment can minimise the impacts due to these variations. This work proposes a novel framework which leverages the information from multi-sensor channels in a combined manner to customise the environment so that situational awareness (SA) can be improved. The proposed framework allows for monitoring the environment by combining the information from different sensor channels including both personal sensors (i.e. on board of a mobile device) as well as environmental sensors/actuators (i.e. embedded in smart-buildings). In this preliminary work, the system architecture is introduced. To demonstrate the potential of the proposed system, a case study is also considered through the development of a prototype for a mobile application and by reporting results on a scale model of a smart workplace with customisable environment.",
	url = "http://hdl.handle.net/10125/59845"
}

Filippo Sanfilippo and Kolbjørn Austreng. Enhancing Teaching Methods on Embedded Systems with Project-Based Learning. In Proceeding of the IEEE International Conference on Engineering, Technology and Education (TALE), Wollongong, Australia. 2018, 335–342. PDF BibTeX

@inproceedings{sanfilippo-2018-embedded-systems,
	title = "Enhancing Teaching Methods on Embedded Systems with Project-Based Learning",
	author = "Sanfilippo, Filippo and Austreng, Kolbj{\o}rn",
	booktitle = "Proceeding of the IEEE International Conference on Engineering, Technology and Education (TALE), Wollongong, Australia",
	pages = "335--342",
	year = 2018,
	abstract = "Automation engineering departments must continuously develop their laboratories and pedagogical tools to provide their students with effective study plans. While acquiring state-of-the-art equipment can be financially demanding, an effort is made at the Norwegian University of Science and Technology (NTNU) in Trondheim to provide the students with a hands-on sustainable experience. A strategy that consists of adopting low-cost commercial off-the-shelf (COTS) components for learning purposes is selected. This combines both industry-standard automation controllers, such as Programmable Logic Controller (PLC) technology, as well as novel microcontrollers designed for use in embedded systems education. Specifically, the micro:bit microcontroller based on the nRF51822 system-on-chip (SoC) and designed by the British Broadcasting Corporation (BBC) is adopted. This choice is supported by an agreement between NTNU and the Norwegian company Nordic Semiconductor, which produces the nRF51822 SoC. This paper proposes a novel organisation of the embedded systems module for the engineering cybernetics education curriculum. Students are engaged in both a series of theoretical lectures as well as practical and highly-involving laboratory group projects. The course organisation and main topics as well as result analysis of student surveys are discussed. The survey results indicate that the course organisation and topics are effective for the students.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-enhancing-teaching-methods-on-embedded-systems-with-project-based-learning.pdf"
}

Filippo Sanfilippo. Perception-Driven Obstacle-Aided Locomotion (POAL) of Learning Snake Robots. In Proceeding of the Workshop on Accountability of Artificial Intelligence, Bologna, Italy. 2018, 68–71. URL BibTeX

@inproceedings{sanfilippo-2018-learning-snake,
	title = "Perception-Driven Obstacle-Aided Locomotion (POAL) of Learning Snake Robots",
	author = "Sanfilippo, Filippo",
	booktitle = "Proceeding of the Workshop on Accountability of Artificial Intelligence, Bologna, Italy",
	pages = "68--71",
	year = 2018,
	organization = "Society for Design and Process Science (SDPS)",
	abstract = "Snake robots equipped with sensors and tools could potentially contribute to applications such as fire-fighting, industrial inspection, search-and-rescue and more. Such capabilities would require that a snake robot has a high degree of awareness of its surroundings (e.g. perception-driven loco- motion) and is able to exploit objects and irregularities in its environment to gain propulsion (e.g. obstacle-aided locomotion). To capture this concept for snake robots, the terms perception- driven obstacle-aided locomotion (POAL) was introduced in literature. Based on several years of research in snake robotics and on recent results, it is possible to state that even though simplified snake robot models were successfully designed, there is still a lack of generality for practical applications. A more flexible and general approach to the problem is needed. POAL is an extremely challenging problem to tackle with traditional control schemes. Based on current trends in robotics, machine learning (e.g. deep learning) approaches may have a great potential for such problem. In this paper, the potentials of adopting machine learning approaches for achieving POAL are discussed.",
	url = "https://www.sdpsnet.org/sdps/documents/sdps-2018/SDPS\%202018\%20proceedings\%20ver\%205.pdf#20"
}

Inaki Rañó, Augusto Gómez Eguiluz and Filippo Sanfilippo. Bridging the Gap Between Bio-inspired Steering and Locomotion: a Braitenberg Snake Robot. In Proceeding of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore. 2018, 1394–1399. PDF BibTeX

@inproceedings{sanfilippo-2018-braitenberg-snake-robot,
	title = "Bridging the Gap Between Bio-inspired Steering and Locomotion: a Braitenberg Snake Robot",
	author = "Ra\~n\'o, Inaki and G{\'o}mez Eguiluz, Augusto and Sanfilippo, Filippo",
	booktitle = "Proceeding of the 15th International Conference on Control, Automation, Robotics and Vision (ICARCV), Singapore",
	pages = "1394--1399",
	year = 2018,
	organization = "IEEE",
	abstract = "Braitenberg vehicles are simple models of animal motion towards, or away from, a stimulus (light, sound, chemicals, etc). They have been widely used in robotics to implement target reaching and avoidance behaviors based on different types of sensors. While the seminal work of Braitenberg used wheeled vehicles to illustrate the principles of animal steering, few attempts have been made at combining these steering level controllers with locomotion mechanism other than actuated wheels. This paper presents the first implementation of this biologically inspired steering controller in a snake-like robot with non-actuated wheels and actuated joints. The sinusoidal gait of the snake is modulated following the principles of the Braitenberg vehicle 3a using two sensors symmetrically located on the head. The effectiveness of this bio-inspired controller is shown through simulations where the snake orients its head and body with the direction of the stimulus gradient, and reaches the stimulus maximum within some range. This paper represents one of the first steps towards connecting bio-inspired sensor-based steering mechanisms and bio-inspired locomotion, and shows that existing theoretical results of Braitenberg vehicles with actuated wheels also apply to a snake-like robot with non-actuated wheels.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-bridging-the-gap-between-bio-inspired-steering-and-locomotion-a-braitenberg-snake-robot.pdf"
}

Filippo Sanfilippo and Claudio Pacchierotti. A Wearable Haptic System for the Health Monitoring of Elderly People in Smart Cities. International Journal of Online Engineering (iJOE) 14(08):52–66, August 2018. URL PDF, DOI BibTeX

@article{sanfilippo-2018-a-wearable-haptic-system-for-the-health-monitoring-of-elderly-people-in-smart-cities,
	author = "Sanfilippo, Filippo and Pacchierotti, Claudio",
	title = "A Wearable Haptic System for the Health Monitoring of Elderly People in Smart Cities",
	journal = "International Journal of Online Engineering (iJOE)",
	year = 2018,
	month = "August",
	volume = 14,
	number = 08,
	pages = "52--66",
	abstract = "A sensor-fusion wearable health-monitoring system with integrated haptic feedback was previously introduced by our research group. The system's components are the following: a chest-worn device with an embedded controller board, an electrocardiogram (ECG) sensor, a temperature sensor, an accelerometer, a vibration motor, a colour-changing light-emitting diode (LED) and a push-button. This multi-sensor device makes possible to collect biometric and medical monitoring data from its wearer. The data provide a real-time indication of the wearer's health state and can also be further analysed later for medical diagnosis. The embedded vibration motor can actuate distinctive haptic feedback patterns according to the wearer's health state. The embedded colour-changing LED provides the wearer with an additional intuitive visual feedback of the current health state, and the wearer can report a potential emergency condition by using the push-button. In this paper, a conceptual case study is presented concerning possible applications for the health monitoring of elderly people in smart cities. The proposed system aims at reducing risk by assessing individual and overall potentially-harmful situations. A data collection and analysis are also presented to demonstrate that the system can provide compelling vibrotactile feedback.",
	url = "http://journals.sfu.ca/onlinejour/index.php/i-joe/article/view/8571",
	keywords = "sensor fusion; wearable; health monitoring; elderly",
	doi = "10.3991/ijoe.v14i08.8571",
	issn = "1861-2121",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-2018-a-wearable-haptic-system-for-the-health-monitoring-of-elderly-people-in-smart-cities.pdf"
}

Filippo Sanfilippo, Øyvind Stavdahl and PÅl Liljebäck. SnakeSIM: a ROS-based control and simulation framework for perception-driven obstacle-aided locomotion of snake robots. Artificial Life and Robotics, pages 1–10, August 2018. URL PDF, DOI BibTeX

@article{sanfilippo2018-snakeSIM-a-ROS-based-control-and-simulation-framework-for-perception-driven-obstacle-aided-locomotion-of-snake-robots,
	author = {Sanfilippo, Filippo and Stavdahl, {\O}yvind and Liljeb{\"a}ck, P{\aa}l},
	title = "{SnakeSIM}: a {ROS}-based control and simulation framework for perception-driven obstacle-aided locomotion of snake robots",
	journal = "Artificial Life and Robotics",
	year = 2018,
	publisher = "Springer",
	month = "August",
	day = 22,
	pages = "1--10",
	abstract = "Biological snakes are capable of exploiting roughness in the terrain for locomotion. This feature allows them to adapt to different types of environments. Snake robots that can mimic this behaviour could be fitted with sensors and used for transporting tools to hazardous or confined areas that other robots and humans are unable to access. Snake robot locomotion in a cluttered environment where the snake robot utilises a sensory--perceptual system to perceive the surrounding operational environment for means of propulsion can be defined as perception-driven obstacle-aided locomotion (POAL). The initial testing of new control methods for POAL in a physical environment using a real snake robot imposes challenging requirements on both the robot and the test environment in terms of robustness and predictability. This paper introduces SnakeSIM, a virtual rapid-prototyping framework that allows researchers for the design and simulation of POAL more safely, rapidly and efficiently. SnakeSIM is based on the robot operating system (ROS) and it allows for simulating the snake robot model in a virtual environment cluttered with obstacles. The simulated robot can be equipped with different sensors. Tactile perception can be achieved using contact sensors to retrieve forces, torques, contact positions and contact normals. A depth camera can be attached to the snake robot head for visual perception purposes. Furthermore, SnakeSIM allows for exploiting the large variety of robotics sensors that are supported by ROS. The framework can be transparently integrated with a real robot. To demonstrate the potential of SnakeSIM, a possible control approach for POAL is considered as a case study.",
	url = "https://doi.org/10.1007/s10015-018-0458-6",
	doi = "10.1007/s10015-018-0458-6",
	issn = "1614-7456",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo2018-snakeSIM-a-ROS-based-control-and-simulation-framework-for-perception-driven-obstacle-aided-locomotion-of-snake-robots.pdf"
}

Filippo Sanfilippo, Øyvind Stavdahl and Pål Liljebäck. SnakeSIM: a ROS-based Rapid-Prototyping Framework for Perception-Driven Obstacle-Aided Locomotion of Snake Robots. In Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China. 2017, 1226–1231. PDF BibTeX

@inproceedings{sanfilippo-2017-ros-snakesim-snake-robots-for-perception-driven-obstacle-aided-locomotion,
	title = "SnakeSIM: a ROS-based Rapid-Prototyping Framework for Perception-Driven Obstacle-Aided Locomotion of Snake Robots",
	author = {Sanfilippo, Filippo and Stavdahl, {\O}yvind and Liljeb{\"a}ck, P\r{a}l},
	booktitle = "Proceeding of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Macau, China",
	pages = "1226--1231",
	year = 2017,
	organization = "IEEE",
	abstract = "Snake robot locomotion in cluttered environments where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion can be defined as perception-driven obstacle-aided locomotion (POAL). The development of POAL is challenging. Moreover, testing new control methods for POAL in a real setup environment is very difficult because potential collisions may damage both the robot and the surrounding environment. In this perspective, a realistic simulator framework may enable researchers to develop control algorithms for POAL more safely, rapidly and efficiently. This paper introduces SnakeSIM, a virtual rapid-prototyping framework that allows researchers for the design and simulation of control algorithms for POAL. To demonstrate the potential of SnakeSIM, a possible control approach for POAL is also considered as a case study.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-snakesim-a-ros-based-rapid-prototyping-framework-for-perception-driven-obstacle-aided-locomotion-of-snake-robots.pdf"
}

Filippo Sanfilippo, Øyvind Stavdahl and Pål Liljebäck. SnakeSIM: a Snake Robot Simulation Framework for Perception-Driven Obstacle-Aided Locomotion. In Proceeding of the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM), Kyoto, Japan. 2017, 86–88. PDF BibTeX

@inproceedings{sanfilippo-2017-snakesim-snake-robots-for-perception-driven-obstacle-aided-locomotion,
	title = "SnakeSIM: a Snake Robot Simulation Framework for Perception-Driven Obstacle-Aided Locomotion",
	author = {Sanfilippo, Filippo and Stavdahl, {\O}yvind and Liljeb{\"a}ck, P\r{a}l},
	booktitle = "Proceeding of the 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics (SWARM), Kyoto, Japan",
	pages = "86--88",
	year = 2017,
	abstract = "Snake robot locomotion in cluttered environments where the snake robot utilises a sensory-perceptual system to perceive the surrounding operational environment for means of propulsion can be defined as perception-driven obstacle-aided locomotion (POAL). The development of POAL is challenging. Moreover, testing new control methods for POAL in a real setup environment is very difficult because potential collisions may damage both the robot and the surrounding environment. In this perspective, a realistic simulator framework may enable researchers to develop control algorithms for POAL more safely, rapidly and efficiently. This paper introduces SnakeSIM, a virtual rapid-prototyping framework that allows researchers for the design and simulation of control algorithms for POAL. To demonstrate the potential of SnakeSIM, a possible control approach for POAL is also considered as a case study.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-2017-snakesim-snake-robots-for-perception-driven-obstacle-aided-locomotion.pdf"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Kristin Ytterstad Pettersen and Houxiang Zhang. A Benchmarking Framework for Control Methods of Maritime Cranes Based on the Functional Mockup Interface. IEEE Journal of Oceanic Engineering PP(99):1-16, March 2017. URL PDF, DOI BibTeX

@article{sanfilippo2017a-benchmarking-framework-for-control-methods-of-maritime-cranes-based-on-the-functional-mockup-interface,
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Pettersen, Kristin Ytterstad and Zhang, Houxiang",
	title = "A Benchmarking Framework for Control Methods of Maritime Cranes Based on the Functional Mockup Interface",
	journal = "IEEE Journal of Oceanic Engineering",
	year = 2017,
	month = "March",
	volume = "PP",
	number = 99,
	pages = "1-16",
	abstract = "A benchmark framework for advanced control methods of maritime cranes is presented based on the use of the functional mockup interface. The system integrates different manipulator models, all the corresponding hydraulic systems, various vessels, and the surrounding environment for visualization. Different control methods can be transparently implemented and tested. A set of routine tests, different cost functions, and metrics are provided—taking into account several factors, including position accuracy, energy consumption, quality, and safety for both the cranes and the surrounding environment. The concept of operational profiles is introduced, allowing for definition of different standard transporting and lifting operations. By considering task-oriented routines, this benchmark suite allows the comparison of different control methods independently from the specific crane model to be controlled. Two alternative control methods for maritime cranes based on the use of artificial intelligence are extensively compared. The first method is based on the use of genetic algorithms, while the second method involves the use of particle swarm optimization. Simulation results are presented for both methods.",
	url = "http://ieeexplore.ieee.org/document/7906482/",
	keywords = "Benchmark testing;Cranes;Hydraulic systems;Manipulators;Standards;Visualization;Maritime cranes;artificial intelligence (AI);benchmark;control methods;functional mockup interface (FMI);machine learning",
	doi = "10.1109/JOE.2017.2691920",
	issn = "0364-9059",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-2017-a-benchmarking-framework-for-control-methods-of-maritime-cranes-based-on-the-functional-mockup-interface.pdf"
}

Filippo Sanfilippo, Jon Azpiazu, Giancarlo Marafioti, Aksel A Transeth, Øyvind Stavdahl and Pål Liljebäck. Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities. Applied Sciences 7(4)(336):1-22, March 2017. URL BibTeX

@article{sanfilippo2017perception-driven-obstacle-aided-locomotion-for-snake-robots,
	author = {Sanfilippo, Filippo and Azpiazu, Jon and Marafioti, Giancarlo and Transeth, Aksel A. and Stavdahl, {\O}yvind and Liljeb{\"a}ck, P\r{a}l},
	title = "Perception-Driven Obstacle-Aided Locomotion for Snake Robots: The State of the Art, Challenges and Possibilities",
	journal = "Applied Sciences",
	year = 2017,
	month = "March",
	volume = "7(4)",
	number = 336,
	pages = "1-22",
	abstract = "In nature, snakes can gracefully traverse a wide range of different and complex environments. Snake robots that can mimic this behaviour could be fitted with sensors and transport tools to hazardous or confined areas that other robots and humans are unable to access. In order to carry out such tasks, snake robots must have a high degree of awareness of their surroundings (i.e., perception-driven locomotion) and be capable of efficient obstacle exploitation (i.e., obstacle-aided locomotion) to gain propulsion. These aspects are pivotal in order to realise the large variety of possible snake robot applications in real-life operations such as fire-fighting, industrial inspection, search-and-rescue, and more. In this paper, we survey and discuss the state of the art, challenges, and possibilities of perception-driven obstacle-aided locomotion for snake robots. To this end, different levels of autonomy are identified for snake robots and categorised into environmental complexity, mission complexity, and external system independence. From this perspective, we present a step-wise approach on how to increment snake robot abilities within guidance, navigation, and control in order to target the different levels of autonomy. Pertinent to snake robots, we focus on current strategies for snake robot locomotion in the presence of obstacles. Moreover, we put obstacle-aided locomotion into the context of perception and mapping. Finally, we present an overview of relevant key technologies and methods within environment perception, mapping, and representation that constitute important aspects of perception-driven obstacle-aided locomotion.",
	url = "http://www.mdpi.com/2076-3417/7/4/336/"
}

Filippo Sanfilippo. A Multi-Sensor Fusion Framework for Improving Situational Awareness in Demanding Maritime Training. Reliability Engineering & System Safety 161:12-24, 2017. URL PDF, DOI BibTeX

@article{sanfilippo2017a-multi-sensor-fusion-framework-for-improving-situational-awareness-in-demanding-maritime training,
	author = "Sanfilippo, Filippo",
	title = "A Multi-Sensor Fusion Framework for Improving Situational Awareness in Demanding Maritime Training",
	journal = "Reliability Engineering & System Safety",
	year = 2017,
	volume = 161,
	pages = "12-24",
	abstract = "Real offshore operational scenarios can involve a considerable amount of risk. Sophisticated training programmes involving specially designed simulator environments constitute a promising approach for improving an individual's perception and assessment of dangerous situations in real applications. One of the world's most advanced providers of simulators for such demanding offshore operations is the Offshore Simulator Centre \{AS\} (OSC). However, even though the \{OSC\} provides powerful simulation tools, techniques for visualising operational procedures that can be used to further improve Situational awareness (SA), are still lacking. Providing the \{OSC\} with an integrated multi-sensor fusion framework is the goal of this work. The proposed framework is designed to improve planning, execution and assessment of demanding maritime operations by adopting newly-designed risk-evaluation tools. Different information from the simulator scene and from the real world can be collected, such as audio, video, bio-metric data from eye-trackers, other sensor data and annotations. This integration is the base for research on novel \{SA\} assessment methodologies. This will serve the industry for the purpose of improving operational effectiveness and safety through the use of simulators. In this work, a training methodology based on the concept of briefing/debriefing is adopted based on previous literature. By using this methodology borrowed from similarly demanding applications, the efficiency of the proposed framework is validated in a conceptual case study. In particular, the training procedure, which was previously performed by Statoil and partners, for the world's first sub-sea gas compression plant, in Aasgard, Norway, is considered and reviewed highlighting the potentials of the proposed framework.",
	url = "http://www.sciencedirect.com/science/article/pii/S0951832016310298",
	issn = "0951-8320",
	doi = "10.1016/j.ress.2016.12.015",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-a-multi-sensor-fusion-framework-for-improving-situational-awareness-in-demanding-maritime-training.pdf"
}

Filippo Sanfilippo, Øyvind Stavdahl, Giancarlo Marafioti, Aksel A Transeth and Pål Liljebäck. Virtual Functional Segmentation of Snake Robots for Perception-Driven Obstacle-Aided Locomotion. In Proceeding of the IEEE Conference on Robotics and Biomimetics (ROBIO), Qingdao, China. 2016, 1845–1851. PDF BibTeX

@inproceedings{sanfilippo-2016-virtual-functional-segmentation-of-snake-robots-for-perception-driven-obstacle-aided-locomotion,
	title = "Virtual Functional Segmentation of Snake Robots for Perception-Driven Obstacle-Aided Locomotion",
	author = {Sanfilippo, Filippo and Stavdahl, {\O}yvind and Marafioti, Giancarlo and Transeth, Aksel A. and Liljeb{\"a}ck, P\r{a}l},
	booktitle = "Proceeding of the IEEE Conference on Robotics and Biomimetics (ROBIO), Qingdao, China",
	pages = "1845--1851",
	year = 2016,
	organization = "IEEE",
	abstract = "Snake robots equipped with sensors and tools could potentially contribute to applications such as fire-fighting, industrial inspection, search-and-rescue and more. Such capabilities would require that a snake robot has a high degree of awareness of its surroundings (i.e. perception-driven locomotion) and is able to exploit objects and irregularities in its environment to gain propulsion (i.e. obstacle-aided locomotion). In this work, a simplified snake robot model is proposed to deal with a lower-dimensional system that allows for establishing the foundation elements of perception-driven obstacle-aided locomotion. To achieve this, a virtual partitioning of the snake into parametrised virtual functional segments (VFS) is presented based on the concept of virtual constraints (VC). The snake robot body is approximated by using a chain of continuous curves with the fewest possible parameters. These parameters can be treated as degrees of freedom of a ``constrained system'' and consequently be subjected to modelling and control at a higher abstraction level. The main contribution of the proposed conceptual approach is that the robot joint space can be reduced into a lower-dimensional space for articulation. This concept replaces the analysis of the individual mechanical degrees of freedom of the snake by the analysis of the functional roles of the parametrised VFS. The VFS are defined in relation to task space coordinates, and the roles of the physical links and joints change according to a defined set of transition events as they move along the robot's path. This method is a preliminary step towards realising perception-driven obstacle-aided locomotion for snake robots.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-2016-virtual-functional-segmentation-of-snake-robots-for-perception-driven-obstacle-aided-locomotion.pdf"
}

Filippo Sanfilippo, Jon Azpiazu, Giancarlo Marafioti, Aksel A Transeth, Øyvind Stavdahl and Pål Liljebäck. A Review on Perception-driven Obstacle-aided Locomotion for Snake Robots. In Proceeding of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand. 2016. PDF BibTeX

@inproceedings{sanfilippo-2016-perception-driven-obstacle-aided-locomotion,
	title = "A Review on Perception-driven Obstacle-aided Locomotion for Snake Robots",
	author = {Sanfilippo, Filippo and Azpiazu, Jon and Marafioti, Giancarlo and Transeth, Aksel A. and Stavdahl, {\O}yvind and Liljeb{\"a}ck, P\r{a}l},
	booktitle = "Proceeding of the 14th IEEE International Conference on Control, Automation, Robotics and Vision (ICARCV), Phuket, Thailand",
	year = 2016,
	organization = "IEEE",
	abstract = "Biological snakes can gracefully traverse a wide range of different and complex environments. Snake robots that can mimic this behaviour could be fitted with sensors and also transport tools to hazardous or confined areas that other robots and humans are unable to access. To carry out such tasks, snake robots must have a high degree of awareness of their surroundings (i.e. perception-driven locomotion) and be capable of efficient obstacle exploitation (i.e. obstacle-aided locomotion) to gain propulsion. These aspects are important to realise the large variety of possible snake robot applications in real-life operations such as fire-fighting, industrial inspection, search-and-rescue and more. In this paper, an elaborate review and discussion of the state-of-the-art, challenges and possibilities of perception-driven obstacle-aided locomotion for snake robots is presented for the first time. Pertinent to snake robots, we focus on current strategies for obstacle avoidance, obstacle accommodation, and obstacle-aided locomotion. Moreover, we put obstacle-aided locomotion into the context of perception and mapping. To this end, we present an overview of relevant key technologies and methods within environment perception, mapping and representation that constitute important aspects of perception-driven obstacle-aided locomotion.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-2016-perception-driven-obstacle-aided-locomotion.pdf"
}

Rafael Sanchez Souza, Filippo Sanfilippo, José Reinaldo Silva and Arturo Forner-Cordero. Modular Exoskeleton Design: Requirement Engineering with KAOS. In Proceeding of the 6th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Singapore. 2016, 978–983. URL PDF BibTeX

@inproceedings{sanfilippo-2016-modular-exoskeleton,
	title = "Modular Exoskeleton Design: Requirement Engineering with KAOS",
	author = "Sanchez Souza, Rafael and Sanfilippo, Filippo and Silva, Jos\'e Reinaldo and Forner-Cordero, Arturo",
	booktitle = "Proceeding of the 6th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Singapore",
	pages = "978--983",
	year = 2016,
	organization = "IEEE RAS & EMBS",
	abstract = "Wearable robots, such as exoskeletons, interact closely with the wearer. To this end, mechanical features are combined with control techniques to transparently follow human movements. Such expected behaviour depends on special project requirements, safety being the most critical one. According to the literature, the modular robot design approach provides flexible and yet robust solutions that meets stakeholder requirements. The semi-formal design approach has been exploited by the scientific community to specifically focus on requirements definition. In this perspective, Goal Oriented Requirement Engineering (GORE) has been used as a tool for different systems; however, it has been more widely adopted in software rather than in hardware engineering. In this paper, GORE is adopted, with the KAOS tool, to fully exploit the integrated design of a modular exoskeleton - an adaptive mechatronic system. The balance of requirements with user safety constraints are analysed to advance in the project initial steps. It is shown that, although requirement modelling requires of an initial effort from the designer regarding goals formulation, the proposed approach provides a more comprehensive system overview and documentation. Finally, the adoption of a semi-formal language justifies why a modular exoskeleton is a good choice when design at meeting stakeholder requirements and improving user experience.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/modular-exoskeleton-design-requirement-engineering-with-kaos.pdf",
	url = "https://doi.org/10.1109/BIOROB.2016.7523756"
}

Filippo Sanfilippo. A Multi-Sensor System for Enhancing Situational Awareness in Offshore Training. In Proceeding of the IEEE International Conference On Cyber Situational Awareness, Data Analytics And Assessment (CyberSA), London, United Kingdom. 2016, 1–6. URL PDF BibTeX

@inproceedings{sanfilippo-2016-situational-awareness-offshore-training,
	title = "A Multi-Sensor System for Enhancing Situational Awareness in Offshore Training",
	author = "Sanfilippo, Filippo",
	booktitle = "Proceeding of the IEEE International Conference On Cyber Situational Awareness, Data Analytics And Assessment (CyberSA), London, United Kingdom",
	pages = "1--6",
	year = 2016,
	organization = "IEEE",
	abstract = "Real offshore operational scenarios are particularly risky. Training programmes involving specifically designed simulators constitute a promising approach for improving human reliability and safety in real applications. One of the world's most advanced providers of simulators for such demanding offshore operations is the Offshore Simulator Centre AS (OSC). However, even though the OSC provides powerful simulation tools, techniques for visualising operational procedures that can be used to further improve situational awareness (SA), are still lacking. In this work, an integrated multi-sensor fusion system is integrated with the OSC. The proposed system is designed to improve planning, execution and assessment of demanding maritime operations by adopting newly-designed risk-evaluation tools. Different information from the simulator scene and from the real world can be collected, such as audio, video, bio-metric data from eye-trackers, other sensor data and annotations. This integration is the base for research on novel SA assessment methodologies. A training methodology based on the concept of briefing/debriefing is adopted. By using this methodology, the efficiency of the proposed system is validated in a conceptual case study that considers the training procedure performed by Statoil and partners for the world's first sub-sea gas compression plant, in Aasgard, Norway.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-a-multi-sensor-system-for-enhancing-situational-awareness-in-offshore-training.pdf",
	url = "https://doi.org/10.1109/CyberSA.2016.7503280"
}

Tom Verplaetse, Filippo Sanfilippo, Adrian Rutle, Ottar Laurits Osen and Robin Trulssen Bye. On Usage of EEG Brain Control for Rehabilitation of Stroke Patients. In Proceeding of the 30th European Conference on Modelling and Simulation (ECMS), Regensburg, Germany. 2016, 544–553. URL PDF BibTeX

@inproceedings{sanfilippo-2016-stroke-rehabilitation,
	title = "On Usage of EEG Brain Control for Rehabilitation of Stroke Patients",
	author = "Verplaetse, Tom and Sanfilippo, Filippo and Rutle, Adrian and Osen, Ottar Laurits and Bye, Robin Trulssen",
	booktitle = "Proceeding of the 30th European Conference on Modelling and Simulation (ECMS), Regensburg, Germany",
	pages = "544--553",
	year = 2016,
	organization = "ECMS",
	abstract = "This paper demonstrates rapid prototyping of a stroke rehabilitation system consisting of an interactive 3D virtual reality computer game environment interfaced with an EEG headset for control and interaction using brain waves. The system is intended for training and rehabilitation of partially monoplegic stroke patients and uses low- cost commercial-off-the-shelf products like the Emotiv EPOC EEG headset and the Unity 3D game engine. A number of rehabilitation methods exist that can improve motor control and function of the paretic upper limb in stroke survivors. Unfortunately, most of these methods are commonly characterised by a number of drawbacks that can limit intensive treatment, including being repetitive, uninspiring, and labour intensive; requiring one-on-one manual interaction and assistance from a therapist, often for several weeks; and involve equipment and systems that are complex and expensive and cannot be used at home but only in hospitals and institutions by trained personnel. Inspired by the principles of mirror therapy and game-stimulated rehabilitation, we have developed a first prototype of a game-like computer application that tries to avoid these drawbacks. For rehabilitation purposes, we deprive the patient of the view of the paretic hand while being challenged with controlling a virtual hand in a simulated 3D game environment only by means of EEG brain waves interfaced with the computer. Whilst our system is only a first prototype, we hypothesise that by iteratively improving its design through refinements and tuning based on input from domain experts and testing on real patients, the system can be tailored for being used together with a conventional rehabilitation programme to improve patients' ability to move the paretic limb much in the same vain as mirror therapy. Our proposed system has several advantages, including being game-based, customisable, adaptive, and extendable. In addition, when compared with conventional rehabilitation methods, our system is extremely low-cost and flexible, in particular because patients can use it in the comfort of their homes, with little or no need for professional human assistance. Preliminary tests are carried out to highlight the potential of the proposed rehabilitation system, however, in order to measure its efficiency in rehabilitation, the system must first be improved and then run through an extensive field test with a sufficiently large group of patients and compared with a control group.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/ECMS2016Stroke.pdf",
	url = "http://www.scs-europe.net/dlib/2016/2016-0544.htm"
}

Rolf-Magnus Hjørungdal, Filippo Sanfilippo, Ottar Laurits Osen, Adrian Rutle and Robin Trulssen Bye. A Game-based Learning Framework for Controlling Brain-Actuated Wheelchairs. In Proceeding of the 30th European Conference on Modelling and Simulation (ECMS), Regensburg, Germany. 2016, 554–563. URL PDF BibTeX

@inproceedings{sanfilippo-2016-brain-actuated-wheelchairs,
	title = "A Game-based Learning Framework for Controlling Brain-Actuated Wheelchairs",
	author = "Hj{\o}rungdal, Rolf-Magnus and Sanfilippo, Filippo and Osen, Ottar Laurits and Rutle, Adrian and Bye, Robin Trulssen",
	booktitle = "Proceeding of the 30th European Conference on Modelling and Simulation (ECMS), Regensburg, Germany",
	pages = "554--563",
	year = 2016,
	organization = "ECMS",
	abstract = "Paraplegia is a disability caused by impairment in motor or sensory functions of the lower limbs. Most paraplegic subjects use mechanical wheelchairs for their movement, however, patients with reduced upper limb functionality may benefit from the use of motorised, electric wheelchairs. Depending on the patient, learning how to control these wheelchairs can be hard (if at all possible), time-consuming, demotivating, and to some extent dangerous. This paper proposes a game-based learning framework for training these patients in a safe, virtual environment. Specifically, the framework utilises the Emotiv EPOC EEG headset to enable brain wave control of a virtual electric wheelchair in a realistic virtual world game environment created with the Unity 3D game engine.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/ECMS2016Wheelchair.pdf",
	url = "http://www.scs-europe.net/dlib/2016/2016-0554.htm"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Houxiang Zhang, Massimiliano Fago and Kristin Ytterstad Pettersen. Controlling Kuka Industrial Robots: Flexible Communication Interface JOpenShowVar. IEEE Robotics & Automation Magazine 22(4):96-109, December 2015. URL PDF BibTeX

@article{sanfilippo2015jopenshowvar,
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Zhang, Houxiang and Fago, Massimiliano and Pettersen, Kristin Ytterstad",
	title = "Controlling Kuka Industrial Robots: Flexible Communication Interface JOpenShowVar",
	journal = "IEEE Robotics \& Automation Magazine",
	year = 2015,
	month = "Dec",
	volume = 22,
	number = 4,
	pages = "96-109",
	abstract = "JOpenShowVar is a Java open-source cross-platform communication interface to Kuka industrial robots. This novel interface allows for read-write use of the controlled manipulator variables and data structures. JOpenShowVar, which is compatible with all the Kuka industrial robots that use KUKA Robot Controller version 4 (KR C4) and KUKA Robot Controller version 2 (KR C2), runs as a client on a remote computer connected with the Kuka controller via TCP/IP. Even though only soft real-time applications can be implemented, JOpenShowVar opens up to a variety of possible applications, making the use of various input devices and sensors as well as the development of alternative control methods possible. Four case studies are presented to demonstrate the potential of JOpenShowVar. The first two case studies are open-loop applications, while the last two case studies describe the possibility of implementing closed-loop applications. In the first case study, the proposed interface is used to make it possible for an Android mobile device to control a Kuka KR 6 R900 SIXX (KR AGILUS) manipulator. In the second case study, the same Kuka robot is used to perform a two-dimensional (2-D) line-following task that can be used for applications, such as advanced welding operations. In the third case study, a closed-loop application is developed to control the same manipulator with a Leap Motion controller that supports hand and finger motions as input without requiring contact or touching. In the fourth case study, a bidirectional closed-loop coupling is established between a Force Dimension omega.7 haptic device and the same Kuka manipulator. Related experiments are carried out to validate the efficiency and flexibility of the proposed communication interface.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/controlling-kuka-industrial-robots-flexible-communication-interface-jopenshowvar.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7349325&contentType=Journals+%26+Magazines"
}

Filippo Sanfilippo and Kristin Ytterstad Pettersen. OpenMRH: a Modular Robotic Hand Generator Plugin for OpenRAVE. In Proceeding of the IEEE Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China. 2015, 1–6. PDF BibTeX

@inproceedings{sanfilippo2015openmrh,
	title = "OpenMRH: a Modular Robotic Hand Generator Plugin for OpenRAVE",
	author = "Sanfilippo, Filippo and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the IEEE Conference on Robotics and Biomimetics (ROBIO), Zhuhai, China",
	pages = "1--6",
	year = 2015,
	organization = "IEEE",
	abstract = "In this work, the open-source plugin OpenMRH is presented for the Open Robotics Automation Virtual Environment (OpenRAVE), a simulation environment for testing, developing and deploying motion planning algorithms. The proposed plugin allows for a fast and automated generation of different modular hand models OpenMRH combines virtual-prototyping and modular concepts. Each modular model is generated by applying a dynamically generated code, which is consistent with the standard syntax expected by OpenRAVE for the simulated models. In this way, once the desired model is generated, an instance of OpenRAVE can be launched and the model can be visualised. Alternatively, the modular models can be generated from a user-defined input specified via a graphical user interface (GUI). The generated models can be used for testing, developing and deploying grasp or motion planning algorithms. Two case studies are considered to validate the efficiency of the proposed model generator. In the first case study, a modular robotic hand model is generated with OpenMRH by using user-defined input parameters. In the second case study, another hand model is generated with OpenMRH by using algorithmic defined input parameters.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/openmrh-a-modular-robotic-hand-generator-plugin-for-openrave.pdf"
}

Filippo Sanfilippo, Paul B T Weustink and Kristin Ytterstad Pettersen. A Coupling Library for the Force Dimension Haptic Devices and the 20-sim Modelling and Simulation Environment. In Proceeding of the 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), Yokohama, Japan. 2015, 168–173. PDF BibTeX

@inproceedings{sanfilippo2015haptics,
	title = "A Coupling Library for the Force Dimension Haptic Devices and the 20-sim Modelling and Simulation Environment",
	author = "Sanfilippo, Filippo and Weustink, Paul B. T. and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the 41st Annual Conference of the IEEE Industrial Electronics Society (IECON), Yokohama, Japan",
	pages = "168--173",
	year = 2015,
	organization = "IEEE",
	abstract = "A haptic feedback device is a device that establishes a kinaesthetic link between a human operator and a computer-generated environment. This paper addresses the bidirectional coupling between a commercial off-the-shelf (COTS) haptic feedback device and a general-purpose modelling and simulation environment. In particular, an open-source library is developed to couple the Force Dimension omega.7 haptic device with the 20-sim modelling and simulation environment. The presented coupling interface is also compatible with all the different haptic devices produced by Force Dimension. The proposed integrated haptic interface makes it possible to track the user’s motion, detect collisions between the user-controlled probe and virtual objects, compute reaction forces in response to motion or contacts and exert an intuitive force feedback on the user. A real-time one-to-one correspondence between reality and virtual reality can be transparently created. This allows for a variety of possible applications. Stability issues, performance issues, design and virtual prototyping challenges can be addressed and investigated for research purposes. In addition, design and virtual prototyping are also of interest to industry. Realistic training environments can be developed for the user considering different possible operations and stressing the importance of usability and user experience. Experiments based on using haptics technology in the field of education can also be easily performed. To demonstrate the potential of the proposed coupling, a case study is presented. Related simulations and experimental results are carried out.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-coupling-library-for-the-force-dimension-haptic-devices-and-the-20-sim-modelling-and-simulation-environment.pdf"
}

Filippo Sanfilippo and Kristin Ytterstad Pettersen. A Sensor Fusion Wearable Health-Monitoring System with Haptic Feedback. In Proceeding of the 11th IEEE International Conference on Innovations in Information Technology (IIT’15), Dubai, United Arab Emirates. 2015, 241–245. PDF BibTeX

@inproceedings{sanfilippo2015wearable,
	title = "A Sensor Fusion Wearable Health-Monitoring System with Haptic Feedback",
	author = "Sanfilippo, Filippo and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the 11th IEEE International Conference on Innovations in Information Technology (IIT’15), Dubai, United Arab Emirates",
	pages = "241--245",
	year = 2015,
	organization = "IEEE",
	abstract = "A wearable integrated health-monitoring system is presented in this paper. The system is based on a multi-sensor fusion approach. It consists of a chest-worn device that embeds a controller board, an electrocardiogram (ECG) sensor, a temperature sensor, an accelerometer, a vibration motor, a colour-changing light-emitting diode (LED) and a push-button. This multi-sensor device allows for performing biometric and medical monitoring applications. Distinctive haptic feedback patterns can be actuated by means of the embedded vibration motor according to the user’s health state. The embedded colour-changing LED is employed to provide the wearer with an additional intuitive visual feedback of the current health state. The push-button provided can be pushed by the user to report a potential emergency condition. The collected biometric information can be used to monitor the health state of the person involved in real-time or to get sensitive data to be subsequently analysed for medical diagnosis. In this preliminary work, the system architecture is presented. As a possible application scenario, the health-monitoring of offshore operators is considered. Related initial simulations and experiments are carried out to validate the efficiency of the proposed technology. In particular, the system reduces risk, taking into consideration assessments based on the individual and on overall potentially-harmful situations.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-sensor-fusion-wearable-health-monitoring-system-with-haptic-feedback.pdf"
}

Filippo Sanfilippo, Lars Ivar Hatledal and Kristin Ytterstad Pettersen. A Fully-Immersive Hapto-Audio-Visual Framework for Remote Touch. In Proceeding of the 11th IEEE International Conference on Innovations in Information Technology (IIT’15), Dubai, United Arab Emirates. 2015. PDF BibTeX

@inproceedings{sanfilippo2015touch,
	title = "A Fully-Immersive Hapto-Audio-Visual Framework for Remote Touch",
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the 11th IEEE International Conference on Innovations in Information Technology (IIT’15), Dubai, United Arab Emirates",
	year = 2015,
	organization = "IEEE",
	abstract = "This paper presents the development of an open-source low-cost framework for a fully-immersive haptic, audio and visual experience. This framework is realised by exclusively adopting commercial off-the-shelf (COTS) components and tools. In particular, vibration actuators and open-source electronics are employed in the design of a pair of novel and inexpensive haptic gloves. These gloves allow for establishing a kinesthetic link between a human operator interacting with a computer-generated environment. Remote touch applications are possible. In the context of Smart Cities, this technology may be adopted to enhance the interface between nature and culture by stimulating the senses or as a complement to the landscape.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-fully-immersive-hapto-audio-visual-framework-for-remote-touch.pdf"
}

Filippo Sanfilippo. Alternative and Flexible Control Approaches for Robotic Manipulators: on the Challenge of Developing a Flexible Control Architecture that Allows for Controlling Different Manipulators. Ph.D. dissertation, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Engineering Cybernetics, Trondheim, June 2015. URL PDF BibTeX

@phdthesis{key:sanfilippophdthesis,
	author = "Sanfilippo, Filippo",
	title = "Alternative and Flexible Control Approaches for Robotic Manipulators: on the Challenge of Developing a Flexible Control Architecture that Allows for Controlling Different Manipulators",
	school = "Ph.D. dissertation, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, Department of Engineering Cybernetics",
	year = 2015,
	address = "Trondheim",
	month = "June",
	abstract = "In this work, efficient design methods for robotic manipulators are initially investigated. Successively, the possibility of developing a flexible control architecture that allows for controlling different manipulators by using a universal input device is outlined. The main challenge of doing this consists of finding a flexible way to map the normally fixed DOFs of the input controller to the variable DOFs of the specific manipulator to be controlled. This process has to be realised regardless of the differences in size, kinematic structure, body morphology, constraints and affordances. Different alternative control algorithms are investigated including effective approaches that do not assume a priori knowledge for the Inverse Kinematic (IK) models. These algorithms derive the kinematic properties from biologically-inspired approaches, machine learning procedures or optimisation methods. In this way, the system is able to automatically learn the kinematic properties of different manipulators. Finally, a methodology for performing experimental activities in the area of maritime cranes and robotic arm control is outlined. By combining the rapid-prototyping approach with the concept of interchangeable interfaces, a simulation and benchmarking framework for advanced control methods of maritime cranes and robotic arms is presented.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-alternative-and-flexible-control-methods-for-robotic-manipulators.pdf",
	url = "http://brage.bibsys.no/xmlui/handle/11250/2360280"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Arne Styve, Houxiang Zhang and Kristin Ytterstad Pettersen. Integrated Flexible Maritime Crane Architecture for the Offshore Simulation Centre AS (OSC): A Flexible Framework for Alternative Maritime Crane Control Algorithms. IEEE Journal of Oceanic Engineering PP(99):1-12, 2015. URL BibTeX

@article{sanfilippo2015osc,
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Styve, Arne and Zhang, Houxiang and Pettersen, Kristin Ytterstad",
	title = "Integrated Flexible Maritime Crane Architecture for the Offshore Simulation Centre AS (OSC): A Flexible Framework for Alternative Maritime Crane Control Algorithms",
	journal = "IEEE Journal of Oceanic Engineering",
	year = 2015,
	month = "",
	volume = "PP",
	number = 99,
	pages = "1-12",
	abstract = "The Offshore Simulator Centre AS (OSC) is the world's most advanced provider of simulators for demanding offshore operations. However, even though the OSC provides very powerful simulation tools, it is mainly designed for training purposes and it does not inherently offer any flexible methods concerning the control methodology. In fact, each crane model is controlled with a dedicated control algorithm that cannot be modified, accessed, or replaced at runtime. As a result, it is not possible to dynamically switch between different control methods, nor is it possible to easily investigate alternative control approaches. To overcome these problems, a flexible and general control system architecture that allows for modeling flexible control algorithms of maritime cranes and more generally, robotic arms, was previously presented by our research group. However, in the previous work, a generic game engine was used to visualize the different models. In this work, the flexible and general control system architecture is integrated with a crane simulator developed by the OSC taking full advantage of the provided domain-consistent simulation tools. The Google Protocol Buffers protocol is adopted to realize the communication protocol. This integration establishes the base for the research of alternative control algorithms, which can be efficiently tested in a realistic maritime simulation environment. As a validating case study, an alternative control method based on particle swarm optimization (PSO) is also presented. Related simulations are carried out to validate the efficiency of the proposed integration.",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7156157&contentType=Early+Access+Articles"
}

Lars Ivar Hatledal, Filippo Sanfilippo, Yingguang Chu and Houxiang Zhang. A Voxel-Based Numerical Method for Computing and Visualising the Workspace of Offshore Cranes. In Proceeding of the 34th International Conference on Ocean, Offshore and Arctic Engineering (OMAE), St. John’s, Newfoundland, Canada. 2015, 1–7. URL BibTeX

@inproceedings{sanfilippo2015voxel,
	title = "A Voxel-Based Numerical Method for Computing and Visualising the Workspace of Offshore Cranes",
	author = "Hatledal, Lars Ivar and Sanfilippo, Filippo and Chu, Yingguang and Zhang, Houxiang",
	booktitle = "Proceeding of the 34th International Conference on Ocean, Offshore and Arctic Engineering (OMAE), St. John’s, Newfoundland, Canada",
	pages = "1--7",
	year = 2015,
	organization = "ASME",
	abstract = "Workspace computation and visualisation is one of the most important criteria in offshore crane design in terms of geometry dimensioning, installation feasibility and operational performance evaluation. This paper presents a numerical method for the computation and visualisation of the workspace of offshore cranes. The Working Load Limit (WLL) and the Safe Working Load (SWL) can be automatically determined. A three-dimensional (3D) rectangular grid of voxels is used to describe the properties of the workspace. Firstly, a number of joint configurations are generated by using the Monte Carlo method, which are then mapped from joint to Cartesian space using forward kinematics (FK). The bounding box of the workspace is then derived from these points, and the voxels are distributed on planes inside the box. The method distinguishes voxels by whether they are reachable and if they are on the workspace boundary. The output of the method is an approximation of the workspace volume and point clouds depicting both the reachable space and the boundary of the workspace. Using a third-party software that can work with point clouds, such like MeshLab, a 3D mesh of the workspace can be obtained. A more in-depth description and the pseudo-code of the presented method are presented. As a case study, the workspace of a common type of offshore crane, with three rotational joints, is computed with the proposed method.",
	url = "http://proceedings.asmedigitalcollection.asme.org/proceeding.aspx?articleid=2465407"
}

Filippo Sanfilippo and Kristin Ytterstad Pettersen. XBee Positioning System with Embedded Haptic Feedback for Dangerous Offshore Operations: a Preliminary Study. In Proceeding of the MTS/IEEE Oceans '15 Conference, Genova, Italy. 2015, 1–6. URL PDF BibTeX

@inproceedings{sanfilippo2015xbee,
	title = "XBee Positioning System with Embedded Haptic Feedback for Dangerous Offshore Operations: a Preliminary Study",
	author = "Sanfilippo, Filippo and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the MTS/IEEE Oceans '15 Conference, Genova, Italy",
	pages = "1--6",
	year = 2015,
	organization = "MTS/IEEE",
	abstract = "The problem of identification and isolation of dangerous zones in offshore installations is investigated in this preliminary work. A node positioning algorithm is implemented in order to track and identify the operational movements on board the vessel. This implementation is realised with an XBee network that uses a trilateration method, making it possible to actively monitor and dynamically identify several on board zones in different operational scenarios. The crew members can be given varying degrees of access permissions in accordance with their job duties. In this way, access to dangerous areas can be easily controlled in a modular fashion. Subsequently, the user's risk perception is considered. Traditionally, the responsibility of proper hazard identification is placed on the operators. For this reason, more attention is being given to the way that people think, feel and behave in response to risk. Risk is perceived differently by different people, and in this sense, the user's experience and therefore ability to perceive risk can be greatly improved with the use of haptics. Haptic feedback, also known as haptics, is the use of the sense of touch in a user interface designed in such a way as to provide the user (operator) with additional information. In this work, a vibration motor is embedded in the operator's helmet, thus providing intuitive haptic feedback. The operator perceives different types of risks according to the surrounding areas due to the integration of this technology with the XBee-based positioning algorithm and by using distinctive feedback patterns. Related experiments are carried out to validate the efficiency of the proposed technology. In particular, the presented approach demonstrates a great potential for an effective risk reduction from both an individual as well as an overall evaluation of the potential harm.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/xbee-positioning-system-with-embedded-haptic-feedback-for-dangerous-offshore-operations-a-preliminary-study.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7271241&contentType=Conference+Publications"
}

Yingguang Chu, Lars Ivar Hatledal, Filippo Sanfilippo, Hans Georg Schaathun, Vilmar Æsøy and Houxiang Zhang. Virtual Prototyping System for Maritime Crane Design and Operation Based on Functional Mock-up Interface. In Proceeding of the MTS/IEEE Oceans '15 Conference, Genova, Italy. 2015, 1–4. URL PDF BibTeX

@inproceedings{sanfilippo2015prototyping,
	title = "Virtual Prototyping System for Maritime Crane Design and Operation Based on Functional Mock-up Interface",
	author = "Chu, Yingguang and Hatledal, Lars Ivar and Sanfilippo, Filippo and Schaathun, Hans Georg and \AEs\oy, Vilmar and Zhang, Houxiang",
	booktitle = "Proceeding of the MTS/IEEE Oceans '15 Conference, Genova, Italy",
	pages = "1--4",
	year = 2015,
	organization = "MTS/IEEE",
	abstract = "This paper presents the framework of a virtual prototyping system for the design and simulation of maritime crane operations. By combining the rapid-prototyping approach with the concept of interchangeable interfaces, different demanding operation scenarios can be simulated including models of the corresponding physical systems, the vessel and the surrounding environment. Multiple tradeoffs and alternative solutions can be evaluated during the design phase. This process can be achieved within a short time period, allowing for the reduction of lead-times as well as for the abatement of mistakes or system failures that may otherwise cause fatal accidents in real tests. In addition, the virtual simulator can also be used for training purposes allowing for a substantial improvement in working efficiency and operation safety. The software architecture of the proposed framework is based on the application of the Functional Mock-up Interface standard. This utilises the current available modelling tools and allows for the exchange of dynamic models and for co-simulation of different models according to the current designing needs. The development of the framework and involved modules of maritime crane systems are described. Preliminary simulations are presented to show the effectiveness and flexibility of the proposed framework.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/virtual-prototyping-system-for-maritime-crane-design-and-operation-based-on-functional-mock-up-interface.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7271342&contentType=Conference+Publications"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Houxiang Zhang, Webjørn Rekdalsbakken and Kristin Ytterstad Pettersen. A Wave Simulator and Active Heave Compensation Framework for Demanding Offshore Crane Operations. In Proceeding of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2015), Halifax, Canada. 2015, 1588–1593. URL PDF BibTeX

@inproceedings{sanfilippo2015wave,
	title = "A Wave Simulator and Active Heave Compensation Framework for Demanding Offshore Crane Operations",
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Zhang, Houxiang and Rekdalsbakken, Webj{\o}rn and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE 2015), Halifax, Canada",
	pages = "1588--1593",
	year = 2015,
	organization = "IEEE",
	abstract = "In this work, a framework is presented that makes it possible to reproduce the challenging operational scenario of controlling offshore cranes via a laboratory setup. This framework can be used for testing different control methods and for training purposes. The system consists of an industrial robot, the \textit{Kuka} \textit{KR 6 R900 SIXX (KR AGILUS)} manipulator and a motion platform with three degrees of freedom. This work focuses on the system integration. The motion platform is used to simulate the wave effects, while the robotic arm is controlled by the user with a joystick. The wave contribution is monitored by means of an accelerometer mounted on the platform and it is used as a negative input to the manipulator's control algorithm so that active heave compensation methods can be achieved. Concerning the system architecture, the presented framework is built on open-source software and hardware. The control software is realised by applying strict multi-threading criteria to meet demanding real-time requirements. Related simulations and experimental results are carried out to validate the efficiency of the proposed framework. In particular, it can be certified that this approach allows for an effective risk reduction from both an individual as well as an overall evaluation of the potential harm.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-wave-simulator-and-active-heave-compensation-framework-for-demanding-offshore-crane-operations.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7129518&contentType=Conference+Publications"
}

Filippo Sanfilippo, Houxiang Zhang and Kristin Ytterstad Pettersen. The New Architecture of ModGrasp for Mind-Controlled Low-Cost Sensorised Modular Hands. In Proceeding of the IEEE International Conference on Industrial Technology (ICIT), Seville, Spain. 2015, 524–529. URL PDF BibTeX

@inproceedings{sanfilippo2015modgrasp,
	title = "The New Architecture of ModGrasp for Mind-Controlled Low-Cost Sensorised Modular Hands",
	author = "Sanfilippo, Filippo and Zhang, Houxiang and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the IEEE International Conference on Industrial Technology (ICIT), Seville, Spain",
	pages = "524--529",
	year = 2015,
	organization = "IEEE",
	abstract = "\textit{ModGrasp}, an open-source virtual and physical rapid-prototyping framework that allows for the design, simulation and control of low-cost sensorised modular hands, was previously introduced by our research group. \textit{ModGrasp} combines the rapid-prototyping approach with the modular concept, making it possible to model different manipulator configurations. Virtual and physical prototypes can be linked in a real-time one-to-one correspondence. In this work, the \textit{ModGrasp} communication pattern is improved, becoming more modular, reliable and robust. In the previous version of the framework, each finger of the prototype was controlled by a separate controller board. In this work, each module, or finger link, is independent, being controlled by a self-reliant slave controller board. In addition, a newly redesigned multi-threading and multi-level software architecture with a hierarchical logical organisation is presented. In this regard, a new programming paradigm is delineated. The new architecture opens up to a variety of possible applications. As a case study, a mind-controlled, low-cost modular manipulator is presented. In detail, the user's levels of attention and meditation are monitored by using an electroencephalography (EEG) headset, the \textit{NeuroSky MindWave}. These levels are used as inputs to control the hand. Since the manipulator features 11 DOFs, a synergistic control approach is chosen to map inputs with outputs with such a different dimensionality. Related simulations and experimental results are carried out.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/the-new-architecture-of-modgraspfor-mind-controlled-low-cost-sensorised-modular-hand.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7125152&contentType=Conference+Publications"
}

Filippo Sanfilippo, Houxiang Zhang, Kristin Ytterstad Pettersen, Gionata Salvietti and Domenico Prattichizzo. ModGrasp: an Open-Source Rapid-Prototyping Framework for Designing Low-Cost Sensorised Modular Hands. In Proceeding of the 5th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), São Paulo, Brazil. 2014, 951–957. URL PDF BibTeX

@inproceedings{sanfilippo2014modgrasp,
	title = "ModGrasp: an Open-Source Rapid-Prototyping Framework for Designing Low-Cost Sensorised Modular Hands",
	author = "Sanfilippo, Filippo and Zhang, Houxiang and Pettersen, Kristin Ytterstad and Salvietti, Gionata and Prattichizzo, Domenico",
	booktitle = "Proceeding of the 5th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), S\~ao Paulo, Brazil",
	pages = "951--957",
	year = 2014,
	organization = "IEEE RAS & EMBS",
	abstract = "This paper introduces ModGrasp, an open-source virtual and physical rapid-prototyping framework that allows for the design, simulation and control of low-cost sensorised modular hands. By combining the rapid-prototyping approach with the modular concept, different manipulator configurations can be modelled. A real-time one-to-one correspondence between virtual and physical prototypes is established. Different control algorithms can be implemented for the models. By using a low-cost sensing approach, functions for torque sensing at the joint level, sensitive collision detection and joint compliant control are possible. A 3-D visualization environment provides the user with an intuitive visual feedback. As a case study, a three-fingered modular manipulator is presented. Related simulations are carried out to validate efficiency and flexibility of the proposed rapid-prototyping framework.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/modgrasp-an-open-source-rapid-prototyping-framework-for-designing-low-cost-sensorised-modular-hands.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6913903&contentType=Conference+Publications"
}

Yingguang Chu, Filippo Sanfilippo, Vilmar Æsøy and Houxiang Zhang. An Effective Heave Compensation and Anti-sway Control Approach for Offshore Hydraulic Crane Operations. In Proceeding of the IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China. 2014, 1282–1287. URL PDF BibTeX

@inproceedings{sanfilippo2014heave,
	title = "An Effective Heave Compensation and Anti-sway Control Approach for Offshore Hydraulic Crane Operations",
	author = "Chu, Yingguang and Sanfilippo, Filippo and \AEs\oy, Vilmar and Zhang, Houxiang",
	booktitle = "Proceeding of the IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China",
	pages = "1282--1287",
	year = 2014,
	organization = "IEEE",
	abstract = "Offshore hydraulic cranes are difficult to operate safely, accurately and efficiently due to their heavy structure, large inertia, non-intuitive control interface and load sway issues that result from external disturbances. This paper presents an effective heave compensation and anti-sway control approach for offshore crane operations, which is based on robotic arm kinematics and energy dissipation principles. Unlike common operator-based joint-by-joint control procedures, this automated method is more flexible, allowing for more intuitive crane operations and more accurate positioning of the hoisted load. In particular, a unique feature of this approach is that the two control functions of heave compensation and anti-sway are transparently combined and simulated in an integrated modelling environment. The system architecture integrates the control model for crane operations, the hydraulic system model for hydraulics characteristic analysis, the 3D model of the crane to be controlled, the vessel and the environment for visualization. The proposed control algorithm and simulation model can be extended to any type of crane model regardless of its configuration or degree of freedom (DOF) without influencing the effectiveness of the method. The hydraulic model is built by using Bond Graph elements and integrated with the control model in the 20-sim simulation environment. The crane operation can be simulated and controlled by the operator using a 3-axis joystick, which provides a transparent user interface. Related simulations were carried out to validate the efficiency and flexibility of the system architecture. As a case study, a 3-joints knuckle boom crane was implemented and tested. The simulation results prove the presented control algorithm for heave compensation and anti-sway to be a valid and efficient solution.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/an-effective-heave-compensation-and-anti-sway-control-approach-for-offshore-hydraulic-crane-operations.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6885884&contentType=Conference+Publications"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Houxiang Zhang and Kristin Ytterstad Pettersen. A Mapping Approach for Controlling Different Maritime Cranes and Robots Using ANN. In Proceeding of the IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China. 2014, 594–599. URL PDF BibTeX

@inproceedings{sanfilippo2014mapping,
	title = "A Mapping Approach for Controlling Different Maritime Cranes and Robots Using ANN",
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Zhang, Houxiang and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the IEEE International Conference on Mechatronics and Automation (ICMA), Tianjin, China",
	pages = "594--599",
	year = 2014,
	organization = "IEEE",
	abstract = "A flexible and general control system architecture that allows for modelling, simulation and control of different models of maritime cranes and, more generally, robotic arms was previously presented by our research group. Each manipulator can be controlled by using the same universal input device regardless of differences in size, kinematic structure, degrees of freedom (DOFs), body morphology, constraints and affordances. The architecture presented establishes the base for the research of a flexible mapping procedure between a universal input device and the manipulators to be controlled, which is the topic of this paper. Based on the same architecture, as a validating case study, a new method for implementing such a mapping algorithm is introduced in this paper. This method is based on the use of Artificial Neural Networks. Using this approach, the system is able to automatically learn the inverse kinematic properties of different models. Learning is done iteratively based only on observation of input-output relationship, unlike most other control schemes. Related simulations are carried out to validate the efficiency of the proposed mapping method.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/a-mapping-approach-for-controlling-different-maritime-cranes-and-robots-using-ann.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6885764&contentType=Conference+Publications"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Houxiang Zhang, Massimiliano Fago and Kristin Ytterstad Pettersen. JOpenShowVar: an Open-Source Cross-Platform Communication Interface to Kuka Robots. In Proceeding of the IEEE International Conference on Information and Automation (ICIA), Hailar, China. 2014, 1154–1159. URL PDF BibTeX

@inproceedings{sanfilippo2014jopenshowvar,
	title = "JOpenShowVar: an Open-Source Cross-Platform Communication Interface to Kuka Robots",
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Zhang, Houxiang and Fago, Massimiliano and Pettersen, Kristin Ytterstad",
	booktitle = "Proceeding of the IEEE International Conference on Information and Automation (ICIA), Hailar, China",
	pages = "1154--1159",
	year = 2014,
	organization = "IEEE",
	abstract = "This paper introduces JOpenShowVar, a Java open-source cross-platform communication interface to Kuka robots that allows for reading and writing variables and data structures of the controlled manipulators. This interface, which is compatible with all Kuka robots that use KR C4 and previous versions, runs as a client on a remote computer connected with the Kuka controller via TCP/IP. JOpenShowVar opens up to a variety of possible applications making it possible to use different input devices, sensors and to develop alternative control methods. To show the potential of the proposed interface, two case studies are presented. In the first one, JOpenShowVar is used to control a Kuka KR 6 R900 SIXX (KR AGILUS) robot with an Android mobile device. In the second case study, the same manipulator is controlled with a Leap Motion Controller that supports hand and finger motions as input without requiring contact or touching. Related simulations are carried out to validate efficiency and flexibility of the proposed communication interface.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/jopenshowvar-an-open-source-cross-platform-communication-interface-to-kuka-robots.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6932823&contentType=Conference+Publications"
}

Lars Ivar Hatledal, Filippo Sanfilippo and Houxiang Zhang. JIOP: a Java Intelligent Optimisation and Machine Learning Framework. In Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy. 2014, 101–107. URL PDF BibTeX

@inproceedings{hatledal2014jiop,
	title = "JIOP: a Java Intelligent Optimisation and Machine Learning Framework",
	author = "Hatledal, Lars Ivar and Sanfilippo, Filippo and Zhang, Houxiang",
	booktitle = "Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy",
	pages = "101--107",
	year = 2014,
	organization = "ECMS",
	abstract = "This paper presents an open source, object-oriented machine learning framework, formally named Java Intelligent Optimisation (JIOP). While JIOP is still in the early stages of development, it already provides a wide variety of general learning algorithms that can be used. Initially designed as a collection of existing learning methods, JIOP aims to emphasise commonalities and dissimilarities of algorithms in order to identify their strengths and weaknesses, providing a simple, coherent and unified view. For this reason, JIOP is suitable for pedagogical purposes, such as for introducing bachelor and master degree students to the concepts of intelligent algorithms. The problems that JIOP aims to solve are initially discussed to demonstrate the need for such a framework. Later on, the design architecture and the current functions of the framework are outlined. As a validating case study, a real application where JIOP is used to minimise the cost function for solving the inverse kinematics (IK) of a KUKA industrial robotic arm with six degrees of freedom (DOF) is also presented. Related simulations are carried out to prove the effectiveness of the proposed framework.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/JIOP_a_Java_Intelligent_Optimisation_and_Machine_Learning_Framework.pdf",
	url = "http://www.scs-europe.net/dlib/2014/2014-0101.htm"
}

Filippo Sanfilippo, Ottar Laurits Osen and Saleh Alaliyat. Recycling a Discarded Robotic Arm for Automation Engineering Education. In Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy. 2014, 81–86. URL PDF BibTeX

@inproceedings{sanfilippo2014recycling,
	title = "Recycling a Discarded Robotic Arm for Automation Engineering Education",
	author = "Sanfilippo, Filippo and Osen, Ottar Laurits and Alaliyat, Saleh",
	booktitle = "Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy",
	pages = "81--86",
	year = 2014,
	organization = "ECMS",
	abstract = "Robotics and automation technology instruction is an important component of the industrial engineering education curriculum. Industrial engineering and automation departments must continuously develop and update their laboratory resources and pedagogical tools in order to provide their students with adequate and effective study plans. While acquiring stateof-the-art manufacturing equipment can be financially demanding, a great effort is made at Aalesund University College to provide the students with an improved hands-on automation integration experience without major capital investments. In particular, a strategy that consists of recycling electronic and robot disposals is adopted. Students are engaged in a real reverse engineering process and then challenged to find new possible applications and uses. By adopting a pedagogical prospective, this paper introduces the design and implementation of a robot control system on a hardware platform based on a Programmable Logic Controller (PLC). In particular, the controlled robot is a Sykerobot 600-5 manipulator with five degrees of freedom (DOFs) that was disposed of by the industry several years ago as electronic waste. Particular emphasis is placed on the pedagogical effectiveness of the proposed control architecture.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Recycling_a_Discarded_Robotic_Arm_for_Automation_Engineering_Education.pdf",
	url = "http://www.scs-europe.net/dlib/2014/2014-0081.htm"
}

Webjørn Rekdalsbakken and Filippo Sanfilippo. Enhancing Undergraduate Research and Learning Methods on Real-Time Processes by Cooperating with Maritime Industries. In Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy. 2014, 108–114. URL PDF BibTeX

@inproceedings{rekdalsbakken2014enhancing,
	title = "Enhancing Undergraduate Research and Learning Methods on Real-Time Processes by Cooperating with Maritime Industries",
	author = "Rekdalsbakken, Webj{\o}rn and Sanfilippo, Filippo",
	booktitle = "Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy",
	pages = "108--114",
	year = 2014,
	organization = "ECMS",
	abstract = "Building embedded real-time systems of guaranteed quality, in a cost-effective manner, raises challenging scientific and technological problems. For several years at Aalesund University College (AAUC), there has been ongoing activity in the development of embedded real time systems in close cooperation with private technology developers from the local industry. Much of this work is related to the design and development of systems for process control and camera surveillance of industrial processes, with an emphasis placed on operations on board ships. The main purpose is to maintain and improve safety and efficiency in industrial and ship operations. A very effective way to meet this goal consists of developing distributed embedded real time systems that independently monitor different dedicated tasks and are integrated in a common ubiquitous network. In this context, bachelor students at AAUC are involved in several research projects that give them the possibility of working in an industrial prospective scenario and under the supervision of both their professors and company-employed engineers. Most often, these activities are also part of an innovative educational and research loop, in which the projects evaluated as having the greatest innovative potential are followed up with new prototypes and research activities. By adopting a pedagogical prospective, this paper introduces an overview of the most promising student projects and methods for including bachelor students in real-time process control research activities is presented. The pedagogical and technological bases of this work are first discussed, and afterwards an analysis is done regarding the importance of COTS (Commercial Off-The-Shelf) products and system integration. Software and communication protocols are discussed from a system integration point of view. Finally, the results and conclusions of this approach are presented.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Enhancing-Undergraduate-Research-and-Learning-Methods-on-Real-Time-Processes-by-Cooperating-with-Maritime-Industries.pdf",
	url = "http://www.scs-europe.net/dlib/2014/2014-0108.htm"
}

Saleh Alaliyat, Harald Yndestad and Filippo Sanfilippo. Optimisation of Boids Swarm Model Based on Genetic Algorithm and Particle Swarm Optimisation Algorithm (Comparative Study). In Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy. 2014, 643–650. URL PDF BibTeX

@inproceedings{alaliyat2014optimisation,
	title = "Optimisation of Boids Swarm Model Based on Genetic Algorithm and Particle Swarm Optimisation Algorithm (Comparative Study)",
	author = "Alaliyat, Saleh and Yndestad, Harald and Sanfilippo, Filippo",
	booktitle = "Proceedings of the 28th European Conference on Modelling and Simulation (ECMS), Brescia, Italy",
	pages = "643--650",
	year = 2014,
	organization = "ECMS",
	abstract = "In this paper, we present two optimisation methods for a generic boids swarm model which is derived from the original Reynolds' boids model to simulate the aggregate moving of a fish school. The aggregate motion is the result of the interaction of the relatively simple behaviours of the individual simulated boids. The aggregate moving vector is a linear combination of every simple behaviour rule vector. The moving vector coefficients should be identified and optimised to have a realistic flocking moving behaviour. We proposed two methods to optimise these coefficients, by using genetic algorithm (GA) and particle swarm optimisation algorithm (PSO). Both GA and PSO are population based heuristic search techniques which can be used to solve the optimisation problems. The experimental results show that optimisation of boids model by using PSO is faster and gives better convergence than using GA.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/Optimisation_of_Boids_Swarm_Model_Based_on_Genetic_Algorithm_and_Particle_Swarm_Optimisation_Algorithm_Comparative_Study.pdf",
	url = "http://www.scs-europe.net/dlib/2014/2014-0643.htm"
}

Filippo Sanfilippo. On the Design of High Quality Sensorised Modular Strollers. Final version 1, Department of Maritime Technology and Operations, Aalesund University College, Norway, March 2014. PDF BibTeX

@techreport{key:sanfilippotechreport,
	author = "Sanfilippo, Filippo",
	title = "On the Design of High Quality Sensorised Modular Strollers",
	institution = "Department of Maritime Technology and Operations, Aalesund University College, Norway",
	year = 2014,
	type = "Final version",
	number = 1,
	address = "Aalesund",
	month = "March",
	note = "This is a proposal presented to Stokke for a virtual and physical rapid-prototyping framework that allows for the simulation and optimal design of high quality sensorised modular strollers.",
	abstract = "A short summary of the publication.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/on-the design-of-high-quality-sensorised-modular-strollers.pdf"
}

Webjørn Rekdalsbakken and Filippo Sanfilippo. Including Bachelor Students in Research Activities in Real-Time Process Control. In Amdam Jørgen, Øyvind Helgesen and Knut-Willy Sæther (eds.). Det Mangfaldige Kvalitetsomgrepet: Fjordantologi 2013. forlag1, January 2014, pages 279–297. PDF BibTeX

@incollection{sanfilippo2014research,
	author = "Rekdalsbakken, Webj{\o}rn and Sanfilippo, Filippo",
	title = "Including Bachelor Students in Research Activities in Real-Time Process Control",
	booktitle = "Det Mangfaldige Kvalitetsomgrepet: Fjordantologi 2013",
	publisher = "forlag1",
	year = 2014,
	editor = "J{\o}rgen, Amdam and Helgesen, {\O}yvind and S{\ae}ther, Knut-Willy",
	type = "Final version",
	pages = "279--297",
	address = "Oslo",
	edition = "First",
	month = "January",
	abstract = "Kvalitet er det samlande omgrepet i denne antologien basert p{\aa} artiklar og posterar presentert p{\aa} Fjordkonferansen 2013. Kvalitet er eit mykje brukt omgrep og blir tolka og forst{\aa}tt p{\aa} ulike m{\aa}tar. Kvalitetsomgrepa nytta i artiklane er sterkt farga av faglege tradisjonar vi finn i forskings- og utdanningsmilj{\o}a p{\aa} Nordvestlandet. Sentralt st{\aa}r sp{\o}rsm{\aa}let ``Kva er kvalitet?'' og med s{\ae}rleg vekt p{\aa}: (1) Kvalitetsvurdering: For {\aa} vurdere om noko er bra eller d{\aa}rleg m{\aa} ein ha eit samanlikningsgrunnlag. (2) Kvalitetsstyring: For betring av kvalitet m{\aa} ein leie eller styre prosessar og tiltak med grunnlag i vurdering av kvalitet. Fjordkonferansen er samlingsstad for utveksling av kunnskap og erfaringar og skal bidra til nettverksbygging mellom fagmilj{\o}a i Sogn og Fjordane og M{\o}re og Romsdal.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/including-bachelor-students-in-research-activities-in-real-time-process-control.pdf"
}

Filippo Sanfilippo, Lars Ivar Hatledal, Hans Georg Schaathun, Kristin Ytterstad Pettersen and Houxiang Zhang. A Universal Control Architecture for Maritime Cranes and Robots Using Genetic Algorithms as a Possible Mapping Approach. In Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, China. 2013, 322–327. URL PDF BibTeX

@inproceedings{sanfilippo2013universal,
	title = "A Universal Control Architecture for Maritime Cranes and Robots Using Genetic Algorithms as a Possible Mapping Approach",
	author = "Sanfilippo, Filippo and Hatledal, Lars Ivar and Schaathun, Hans Georg and Pettersen, Kristin Ytterstad and Zhang, Houxiang",
	booktitle = "Proceedings of the IEEE International Conference on Robotics and Biomimetics (ROBIO), Shenzhen, China",
	pages = "322--327",
	year = 2013,
	organization = "IEEE",
	abstract = "This paper introduces a flexible and general control system architecture that allows for modelling, simulation and control of different models of maritime cranes and, more generally, robotic arms by using the same universal input device regardless of their differences in size, kinematic structure, degrees of freedom, body morphology, constraints and affordances. The manipulators that are to be controlled can be added to the system simply by defining the corresponding Denavit-Hartenberg table and their joint limits. The models can be simulated in a 3D visualisation environment, which provides the user with an intuitive visual feedback. The presented architecture represents the base for the research of a flexible mapping procedure between a universal input device and the manipulators to be controlled. As a case study, our first attempt of implementing such a mapping algorithm is also presented. This method is bio-inspired and it is based on the use of Genetic Algorithms (GA). Using this approach, the system is able to automatically learn the inverse kinematic properties of different models. Related simulations were carried out to validate the efficiency of proposed architecture and mapping method.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-robio2013.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6739479&contentType=Conference+Publications"
}

Filippo Sanfilippo, Hans Petter Hildre, Vilmar Æsøy, Houxiang Zhang and Eilif Pedersen. Flexible Modeling And Simulation Architecture For Haptic Control Of Maritime Cranes And Robotic Arms. In Proceedings of the 27th European Conference on Modelling and Simulation (ECMS), Aalesund, Norway. 2013, 235–242. URL PDF BibTeX

@inproceedings{sanfilippo2013flexible,
	title = "Flexible Modeling And Simulation Architecture For Haptic Control Of Maritime Cranes And Robotic Arms",
	author = "Sanfilippo, Filippo and Hildre, Hans Petter and {\AE}s{\o}y, Vilmar and Zhang, Houxiang and Pedersen, Eilif",
	booktitle = "Proceedings of the 27th European Conference on Modelling and Simulation (ECMS), Aalesund, Norway",
	pages = "235--242",
	year = 2013,
	organization = "ECMS",
	abstract = "This paper introduces a modular prototyping system architecture that allows for the modeling, simulation and control of different maritime cranes or robotic arms with different kinematic structures and degrees of freedom using the Bond Graph Method. The resulting models are simulated in a virtual environment and controlled using the same input haptic device, which also provides the user with a valuable force feedback. The arm joint angles can be calculated at runtime according to the specific model of the robot to be controlled. The idea is to develop a library of crane beams, joints and actuator models that can be used as modules for simulating different cranes. The base module of this architecture is the crane beam model. Using different joint modules to connect several such models, different crane prototypes can be easily built. The library also includes a simplified model of a vessel to which the crane models can be connected in order to get a complete model. Related simulations were carried out using the so-called 20-sim simulator to validate efficiency and flexibility of the proposed architecture. In particular, a two-beam crane model connected to a simplified vessel model was implemented. To control the arm, an omega.7 from Force Dimension was used as an input haptic device.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-ecms2013.pdf",
	url = "http://www.scs-europe.net/dlib/2013/2013-0235.htm"
}

Filippo Sanfilippo, Gionata Salvietti, Houxiang Zhang, Hans Petter Hildre and Domenico Prattichizzo. Efficient modular grasping: An iterative approach. In Proceedings of the 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Rome, Italy. 2012, 1281–1286. URL PDF BibTeX

@inproceedings{sanfilippo2012efficient,
	title = "Efficient modular grasping: An iterative approach",
	author = "Sanfilippo, Filippo and Salvietti, Gionata and Zhang, Houxiang and Hildre, Hans Petter and Prattichizzo, Domenico",
	booktitle = "Proceedings of the 4th IEEE RAS \& EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob), Rome, Italy",
	pages = "1281--1286",
	year = 2012,
	organization = "IEEE",
	abstract = {This paper introduces a new modular approach to robotic grasping that allows for finding a trade off between a simple gripper and more complex human like manipulators. The modular approach to robotic grasping aims to understand human grasping behavior in order to replicate grasping and skilled in-hand movements with an artificial hand using simple, robust, and flexible modules. In this work, the design of modular grasping devices capable of adapting to different requirements and situations is investigated. A novel algorithm that determines effective modular configurations to get efficient grasps of given objects is presented. The resulting modular configurations are able to perform effective grasps that a human would consider "stable". Related simulations were carried out to validate the efficiency of the algorithm. Preliminary results show the versatility of the modular approach in designing grippers.},
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-biorob2012.pdf",
	url = "http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6290693&contentType=Conference+Publications"
}

Cong Liu, Filippo Sanfilippo, Houxiang Zhang, Hans Petter Hildre, Chang Liu and Shusheng Bi. Locomotion Analysis of a Modular Pentapedal Walking Robot. In Proceedings of the 26th European Conference on Modelling and Simulation (ECMS), Koblenz, Germany. 2012, 441–447. URL PDF BibTeX

@inproceedings{liu2012locomotion,
	title = "Locomotion Analysis of a Modular Pentapedal Walking Robot",
	author = "Liu, Cong and Sanfilippo, Filippo and Zhang, Houxiang and Hildre, Hans Petter and Liu, Chang and Bi, Shusheng",
	booktitle = "Proceedings of the 26th European Conference on Modelling and Simulation (ECMS), Koblenz, Germany",
	pages = "441--447",
	year = 2012,
	organization = "ECMS",
	abstract = "In this paper, the configuration of a five-limbed modular robot is introduced. A specialised locomotion gait is designed to allow for omni-directional mobility. Due to the large diversity resulting from various gait sequences, a criteria for selecting the best gaits based on their stability characteristics is proposed. A series of simulations is then performed to evaluate the various gaits in different walking directions. A gait arrangement scheme toward omni-directional locomotion is finally derived. Lastly, Experiments are also carried out on our pentapedal robot prototype in order to validate the results of simulation. The experiments confirm the gait analysis and selection is highly accurate in the evaluation of gait stability.",
	pdf = "http://www.scs-europe.net/conf/ecms2012/ecms2012%20accepted%20papers/mct_ECMS_0037.pdf",
	url = "http://www.scs-europe.net/dlib/2012/2012-0441.htm"
}

Filippo Sanfilippo. MastersThesis: On the Design of Effective Modular Reconfigurable Grippers: an Iterative Approach. Final version, University of Siena, Siena, Italy, 2011. PDF BibTeX

@mastersthesis{sanfilippo2011design,
	author = "Sanfilippo, Filippo",
	title = "MastersThesis: On the Design of Effective Modular Reconfigurable Grippers: an Iterative Approach",
	school = "University of Siena",
	year = 2011,
	type = "Final version",
	address = "Siena, Italy",
	abstract = "We investigate the possibility of developing a modular robotic gripper that allows for easy adaptation to different requirements and situations. In other words, we de�ne the guidelines for creating a device capable of adapting its structure and functionality to the characteristics of an object or a set of objects to be grasped. An algorithm capable of determining efficient modular gripper configurations to get a stable grasp of given objects is developed.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-msc-thesis.pdf"
}

Filippo Sanfilippo. BachelorsThesis: Real World and Virtual World Architecture for Interconnecting First and Second Life. Final version, University of Catania, Catania, Italy, 2009. PDF BibTeX

@mastersthesis{sanfilippo2009real,
	author = "Sanfilippo, Filippo",
	title = "BachelorsThesis: Real World and Virtual World Architecture for Interconnecting First and Second Life",
	school = "University of Catania",
	year = 2009,
	type = "Final version",
	address = "Catania, Italy",
	abstract = "This thesis researches integrating the real world with virtual worlds where real world data is imported, manipulated and visualised in a virtual world. The overall objective is to create a generic architecture for interconnecting the real and virtual worlds with the end purpose of establishing real-time communications between them.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-bsc-thesis.pdf"
}

MJ Callaghan, JG Harkin, G Scibilia, F Sanfilippo, Kerri McCusker and S Wilson. Experiential based learning in 3D Virtual Worlds: Visualization and data integration in Second Life. In Remote Engineering & Virtual Instrumentation, (REV 2008). 2008. URL PDF BibTeX

@inproceedings{callaghan2008experiential,
	title = "Experiential based learning in 3D Virtual Worlds: Visualization and data integration in Second Life",
	author = "Callaghan, MJ and Harkin, JG and Scibilia, G and Sanfilippo, F and McCusker, Kerri and Wilson, S",
	booktitle = "Remote Engineering \& Virtual Instrumentation, (REV 2008)",
	year = 2008,
	organization = "REV",
	abstract = "This paper investigates the use of the popular virtual world, Second Life, to create experiential based learning experiences in a 3D immersive world for teaching computer hardware and electronic systems. In particular, the paper presents a number of approaches to capturing, displaying and visualizing real world data in such 3D virtual environments.",
	pdf = "http://filipposanfilippo.inspitivity.com/publications/sanfilippo-rev2008.pdf",
	url = "http://eprints.ulster.ac.uk/8821/"
}