Staff profile

Farshad Arvin is a Professor of Robotics in the Department of Computer Science at Durham University.

He received his BSc degree in Computer Engineering in 2004, an MSc degree in Computer Systems Engineering in 2010, and a PhD in Computer Science in 2015.

Background

Before joining Durham in 2022, Farshad was a Lecturer in Robotics (2018-2021) and a Senior Lecturer in Robotics (2021-2022) in the Department of Electrical & Electronic Engineering at The University of Manchester.

He joined the University of Manchester in 2015 as a Post-Doctoral Research Associate in the Robotics for Extreme Environments group at the Department of Electrical & Electronic Engineering. He was a Research Assistant at the Lincoln Centre for Autonomous Systems (L-CAS) at the University of Lincoln, UK (2012 to 2015). He was awarded a Marie Skłodowska-Curie fellowship for being involved in the FP7-EYE2E and LIVCODE EU projects during his PhD study.

Experience

Farshad's research interests include Biohybrid Robotics, Bio-inspired Swarm Robotics, and Autonomous Multi-agent Systems.

He visited several leading institutes, including Artificial Life Laboratory in Karl-Franzens University of Graz, Austria, in 2018; the Italian Institute of Technology (iit) in Genoa, Italy, in 2017; Institute of Rehabilitation and Medical Robotics in Huazhong University of Science and Technology (HUST), Wuhan, China, in 2014; and the Institute of Microelectronics at Tsinghua University in Beijing, China, in 2013 and 2012. 

Research Team and Projects

Farshad is the founding director of Swarm & Computation Intelligence Laboratory (SwaCIL), formed in 2018. The lab hosts 4 Post-Doctoral Research Associates, an Electronics technician and 6 PGR students. It has received more than £4M in direct funding from the EU, EPSRC, InnovateUK and industry. Farshad coordinates several research projects, including a large EU project H2020-FET RoboRoyale (2021-2026, €3.27M), PI in Horizon Europe Pathfiner Sensorbees (2024-2029, €3.2M), PI in Horizon Europe  BioDiMoBot (2025-2030, €8M) and H2020-FET Robocoenosis (2020-2025, €3M).

• Swarm Robotics
• Bio-inspired Swarms
• Multi-agent Systems
• Bio-hybrid Systems

Chapter in book

• Bilaloğlu, C., Şahin, M., Arvin, F., Şahin, E., & Turgut, A. E. (in press). A Novel Time-of-Flight Range and Bearing Sensor System for Micro Air Vehicle Swarms. In Swarm Intelligence. https://doi.org/10.1007/978-3-031-20176-9_20
• Bahaidarah, M., Bana, F. R., Turgut, A. E., Marjanovic, O., & Arvin, F. (in press). Optimization of a Self-organized Collective Motion in a Robotic Swarm. In Swarm Intelligence. https://doi.org/10.1007/978-3-031-20176-9_31

Conference Paper

• Watson, M., Ren, H., Arvin, F., & Hu, J. (2024, August). Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆. Presented at 2024 Annual Conference Towards Autonomous Robotic Systems (TAROS), London
• Champagnie, K., Chen, B., Arvin, F., & Hu, J. (2024, August). Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning. Presented at 2024 IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy
• Agachi, C., Arvin, F., & Hu, J. (2024, August). RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems. Presented at 2024 IEEE International Conference on Intelligent Systems (IS), Varna, Bulgaria
• Champagnie, K., Arvin, F., & Hu, J. (2024, March). Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization. Presented at 2024 IEEE International Conference on Industrial Technology (ICIT), Bristol, UK
• Wu, K., Hu, J., Ding, Z., & Arvin, F. (2023, July). Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems
• Wu, K., Hu, J., Lennox, B., & Arvin, F. (2022, July). Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements. Presented at 2022 European Control Conference (ECC), London, United Kingdom
• Thenius, R., Rajewicz, W., Varughese, J. C., Schoenwetter-Fuchs, S., Arvin, F., Casson, A. J., Wu, C., Lennox, B., Campo, A., van Vuuren, G. J., Stefanini, C., Romano, D., & Schmickl, T. (2021, July). Biohybrid Entities for Environmental Monitoring. Presented at The 2021 Conference on Artificial Life
• Jang, I., Hu, J., Arvin, F., Carrasco, J., & Lennox, B. (2021, August). Omnipotent Virtual Giant for Remote Human–Swarm Interaction. Presented at 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN), Vancouver, BC, Canada
• Arvin, F., Turgut, A. E., Krajnik, T., Rahimi, S., Okay, I. E., Yue, S., Watson, S., & Lennox, B. (2018, October). Φ Clust: Pheromone-Based Aggregation for Robotic Swarms. Presented at 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Madrid, Spain
• Arvin, F., Krajnik, T., Turgut, A. E., & Yue, S. (2015, September). COSΦ: Artificial pheromone system for robotic swarms research. Presented at 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Journal Article

• Hu, J., Turgut, A. E., Krajnik, T., Lennox, B., & Arvin, F. (online). Occlusion-Based Coordination Protocol Design for Autonomous Robotic Shepherding Tasks. IEEE Transactions on Cognitive and Developmental Systems, 14(1), https://doi.org/10.1109/tcds.2020.3018549
• Ulrich, J., Stefanec, M., Rekabi-Bana, F., Fedotoff, L. A., Rouček, T., Gündeğer, B. Y., Saadat, M., Blaha, J., Janota, J., Hofstadler, D. N., Žampachů, K., Keyvan, E. E., Erdem, B., Şahin, E., Alemdar, H., Turgut, A. E., Arvin, F., Schmickl, T., & Krajník, T. (2024). Autonomous tracking of honey bee behaviors over long-term periods with cooperating robots. Science Robotics, 9(95), Article eadn6848. https://doi.org/10.1126/scirobotics.adn6848
• Rekabi Bana, F., Krajník, T., & Arvin, F. (2024). Evolutionary optimization for risk-aware heterogeneous multi-agent path planning in uncertain environments. Frontiers in Robotics and AI, 11, Article 1375393. https://doi.org/10.3389/frobt.2024.1375393
• Sadeghi Amjadi, A., Bilaloğlu, C., Turgut, A. E., Na, S., Şahin, E., Krajník, T., & Arvin, F. (2024). Reinforcement learning-based aggregation for robot swarms. Adaptive Behavior, 32(3), 265-281. https://doi.org/10.1177/10597123231202593
• Chai, R., Niu, H., Carrasco, J., Arvin, F., Yin, H., & Lennox, B. (2024). Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment. IEEE Transactions on Neural Networks and Learning Systems, 35(4), 5778-5792. https://doi.org/10.1109/tnnls.2022.3209154
• Bahaidarah, M., Rekabi-Bana, F., Marjanovic, O., & Arvin, F. (2024). Swarm flocking using optimisation for a self-organised collective motion. Swarm and Evolutionary Computation, 86, Article 101491. https://doi.org/10.1016/j.swevo.2024.101491
• Hu, C., Arvin, F., Bellotto, N., Yue, S., & Li, H. (2024). Editorial: Swarm neuro-robots with the bio-inspired environmental perception. Frontiers in Neurorobotics, 18, Article 1386178. https://doi.org/10.3389/fnbot.2024.1386178
• Rekabi-Bana, F., Hu, J., Krajník, T., & Arvin, F. (2024). Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs. IEEE Transactions on Intelligent Transportation Systems, 25(3), 2492-2507. https://doi.org/10.1109/tits.2023.3320049
• Wu, K., Hu, J., Li, Z., Ding, Z., & Arvin, F. (2024). Distributed Collision-Free Bearing Coordination of Multi-UAV Systems With Actuator Faults and Time Delays. IEEE Transactions on Intelligent Transportation Systems, 1-14. https://doi.org/10.1109/tits.2024.3364356
• Rajewicz, W., Wu, C., Romano, D., Campo, A., Arvin, F., Casson, A. J., Jansen van Vuuren, G., Stefanini, C., Varughese, J. C., Lennox, B., Schönwetter-Fuchs, S., Schmickl, T., & Thenius, R. (2024). Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring. Bioinspiration & Biomimetics, 19(1), Article 015001. https://doi.org/10.1088/1748-3190/ad0c5d
• Xie, S., Hu, J., Ding, Z., & Arvin, F. (2023). Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model. IEEE Transactions on Vehicular Technology, 72(3), 2974 - 2987. https://doi.org/10.1109/tvt.2022.3218575
• Wu, K., Hu, J., Ding, Z., & Arvin, F. (2023). Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements. IEEE Transactions on Automation Science and Engineering, https://doi.org/10.1109/tase.2023.3239748
• Na, S., Roucek, T., Ulrich, J., Pikman, J., Krajnik, T., Lennox, B., & Arvin, F. (2023). Federated Reinforcement Learning for Collective Navigation of Robotic Swarms. IEEE Transactions on Cognitive and Developmental Systems, https://doi.org/10.1109/tcds.2023.3239815
• Xie, S., Hu, J., Bhowmick, P., Ding, Z., & Arvin, F. (2022). Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field. IEEE Transactions on Intelligent Transportation Systems, 23(11), 21531- 21547. https://doi.org/10.1109/tits.2022.3189741
• Hu, J., Lennox, B., & Arvin, F. (2022). Robust formation control for networked robotic systems using Negative Imaginary dynamics. Automatica, 140, Article 110235. https://doi.org/10.1016/j.automatica.2022.110235
• Hu, J., Niu, H., Carrasco, J., Lennox, B., & Arvin, F. (2022). Fault-tolerant cooperative navigation of networked UAV swarms for forest fire monitoring. Aerospace Science and Technology, 123, Article 107494. https://doi.org/10.1016/j.ast.2022.107494
• Na, S., Niu, H., Lennox, B., & Arvin, F. (2022). Bio-Inspired Collision Avoidance in Swarm Systems via Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology, 71(3), 2511-2526. https://doi.org/10.1109/tvt.2022.3145346
• Hu, J., Turgut, A. E., Lennox, B., & Arvin, F. (2022). Robust Formation Coordination of Robot Swarms With Nonlinear Dynamics and Unknown Disturbances: Design and Experiments. IEEE Transactions on Circuits and Systems II: Express Briefs, 69(1), 114-118. https://doi.org/10.1109/tcsii.2021.3074705
• Stefanec, M., Hofstadler, D. N., Krajník, T., Turgut, A. E., Alemdar, H., Lennox, B., Şahin, E., Arvin, F., & Schmickl, T. (2022). A Minimally Invasive Approach Towards “Ecosystem Hacking” With Honeybees. Frontiers in Robotics and AI, 9, Article 791921. https://doi.org/10.3389/frobt.2022.791921
• Ban, Z., Hu, J., Lennox, B., & Arvin, F. (2021). Self-Organised Collision-Free Flocking Mechanism in Heterogeneous Robot Swarms. Mobile Networks and Applications, 26(6), 2461–2471. https://doi.org/10.1007/s11036-021-01785-7
• Hu, J., Bhowmick, P., Jang, I., Arvin, F., & Lanzon, A. (2021). A Decentralized Cluster Formation Containment Framework for Multirobot Systems. IEEE Transactions on Robotics, 37(6), 1936-1955. https://doi.org/10.1109/tro.2021.3071615
• Wu, K., Hu, J., Lennox, B., & Arvin, F. (2021). Finite-Time Bearing-Only Formation Tracking of Heterogeneous Mobile Robots With Collision Avoidance. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(10), 3316-3320. https://doi.org/10.1109/tcsii.2021.3066555
• Na, S., Qiu, Y., Turgut, A. E., Ulrich, J., Krajník, T., Yue, S., Lennox, B., & Arvin, F. (2021). Bio-inspired artificial pheromone system for swarm robotics applications. Adaptive Behavior, 29(4), 395-415. https://doi.org/10.1177/1059712320918936
• Li, P.-Z., Zhang, D.-F., Lennox, B., & Arvin, F. (2021). A 3-DOF piezoelectric driven nanopositioner: Design, control and experiment. Mechanical Systems and Signal Processing, 155, Article 107603. https://doi.org/10.1016/j.ymssp.2020.107603
• Schranz, M., Di Caro, G. A., Schmickl, T., Elmenreich, W., Arvin, F., Şekercioğlu, A., & Sende, M. (2021). Swarm Intelligence and cyber-physical systems: Concepts, challenges and future trends. Swarm and Evolutionary Computation, 60, Article 100762. https://doi.org/10.1016/j.swevo.2020.100762
• Alsayed, A., Yunusa-Kaltungo, A., Quinn, M. K., Arvin, F., & Nabawy, M. R. (2021). Drone-Assisted Confined Space Inspection and Stockpile Volume Estimation. Remote Sensing, 13(17), Article 3356. https://doi.org/10.3390/rs13173356
• Wu, K., Hu, J., Lennox, B., & Arvin, F. (2021). SDP-Based Robust Formation-Containment Coordination of Swarm Robotic Systems with Input Saturation. Journal of Intelligent and Robotic Systems, 102(1), Article 12. https://doi.org/10.1007/s10846-021-01368-4
• Hu, J., Niu, H., Carrasco, J., Lennox, B., & Arvin, F. (2020). Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning. IEEE Transactions on Vehicular Technology, 69(12), https://doi.org/10.1109/tvt.2020.3034800
• Hu, J., Bhowmick, P., Arvin, F., Lanzon, A., & Lennox, B. (2020). Cooperative Control of Heterogeneous Connected Vehicle Platoons: An Adaptive Leader-Following Approach. IEEE Robotics and Automation Letters, 5(2), 977-984. https://doi.org/10.1109/lra.2020.2966412
• Liu, Z., West, C., Lennox, B., & Arvin, F. (2020). Local Bearing Estimation for a Swarm of Low-Cost Miniature Robots. Sensors, 20(11), Article 3308. https://doi.org/10.3390/s20113308
• Li, P.-Z., Zhang, D.-F., Hu, J.-Y., Lennox, B., & Arvin, F. (2020). Hysteresis Modelling and Feedforward Control of Piezoelectric Actuator Based on Simplified Interval Type-2 Fuzzy System. Sensors, 20(9), 2587-2599. https://doi.org/10.3390/s20092587
• Grieve, B. D., Duckett, T., Collison, M., Boyd, L., West, J., Yin, H., Arvin, F., & Pearson, S. (2019). The challenges posed by global broadacre crops in delivering smart agri-robotic solutions: A fundamental rethink is required. Global Food Security, 23, 116-124. https://doi.org/10.1016/j.gfs.2019.04.011
• Arvin, F., Espinosa, J., Bird, B., West, A., Watson, S., & Lennox, B. (2019). Mona: an Affordable Open-Source Mobile Robot for Education and Research. Journal of Intelligent and Robotic Systems, 94(3-4), 761–775. https://doi.org/10.1007/s10846-018-0866-9
• Cheah, W., Khalili, H. H., Arvin, F., Green, P., Watson, S., & Lennox, B. (2019). Advanced motions for hexapods. International Journal of Advanced Robotic Systems, 16(2), https://doi.org/10.1177/1729881419841537
• Arvin, F., Watson, S., Turgut, A. E., Espinosa, J., Krajník, T., & Lennox, B. (2018). Perpetual Robot Swarm: Long-Term Autonomy of Mobile Robots Using On-the-fly Inductive Charging. Journal of Intelligent and Robotic Systems, 92(3-4), https://doi.org/10.1007/s10846-017-0673-8
• Hu, C., Arvin, F., Xiong, C., & Yue, S. (2017). Bio-Inspired Embedded Vision System for Autonomous Micro-Robots: The LGMD Case. IEEE Transactions on Cognitive and Developmental Systems, 9(3), 241-254. https://doi.org/10.1109/tcds.2016.2574624
• Arvin, F., Turgut, A. E., Krajník, T., & Yue, S. (2016). Investigation of cue-based aggregation in static and dynamic environments with a mobile robot swarm. Adaptive Behavior, 24(2), 102-118. https://doi.org/10.1177/1059712316632851
• Arvin, F., Murray, J., Zhang, C., & Yue, S. (2014). Colias: An Autonomous Micro Robot for Swarm Robotic Applications. International Journal of Advanced Robotic Systems, 11(7), https://doi.org/10.5772/58730
• Arvin, F., Turgut, A. E., Bazyari, F., Arikan, K. B., Bellotto, N., & Yue, S. (2014). Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method. Adaptive Behavior, 22(3), 189-206. https://doi.org/10.1177/1059712314528009