All Outputs (50)

Evolutionary optimization for risk-aware heterogeneous multi-agent path planning in uncertain environments (2024)
Journal Article
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

Cooperative multi-agent systems make it possible to employ miniature robots in order to perform different experiments for data collection in wide open areas to physical interactions with test subjects in confined environments such as a hive. This pap... Read More about Evolutionary optimization for risk-aware heterogeneous multi-agent path planning in uncertain environments.

Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆ (2024)
Presentation / Conference Contribution
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

Coverage Path Planning (CPP) is an effective approach to let intelligent robots cover an area by finding feasible paths through the environment. In this paper, we focus on using reinforcement learning to learn about a given environment and find the m... Read More about Predator-Prey Q-Learning Based Collaborative Coverage Path Planning for Swarm Robotics ⋆.

RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems (2024)
Presentation / Conference Contribution
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

Coordination of multi-agent systems has received significant attention during the past few years owing to its wide real-world applications, such as cooperative exploration, aircraft formation, and autonomous vehicle platooning. To address this issue,... Read More about RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems.

Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization (2024)
Presentation / Conference Contribution
Champagnie, K., Arvin, F., & Hu, J. (2024). Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization. In 2024 IEEE International Conference on Industrial Technology (ICIT). https://doi.org/10.1109/ICIT58233.2024.10540869

In this paper, we present GEM, a novel approach to online coverage path planning in which a swarm of homogeneous agents act to maximize the entropy of pheromone deposited within their environment. We show that entropy maximization (EM) coincides with... Read More about Decentralized Multi-Agent Coverage Path Planning with Greedy Entropy Maximization.

Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning (2024)
Presentation / Conference Contribution
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

Two promising approaches to coverage path planning are reward-based and pheromone-based methods. Reward-based methods allow heuristics to be learned automatically, often yielding a superior performance to hand-crafted rules. On the other hand, pherom... Read More about Online Multi-Robot Coverage Path Planning in Dynamic Environments Through Pheromone-Based Reinforcement Learning.

Editorial: Swarm neuro-robots with the bio-inspired environmental perception. (2024)
Journal Article
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

From disaster zone exploration to environmental monitoring, robots capable of navigating complex and unpredictable environments are in high demand. Inspired by the efficiency of insect swarms, the field of neuro-robotics has seen breakthroughs in eff... Read More about Editorial: Swarm neuro-robots with the bio-inspired environmental perception..

Distributed Collision-Free Bearing Coordination of Multi-UAV Systems With Actuator Faults and Time Delays (2024)
Journal Article
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

Coordination of unmanned aerial vehicle (UAV) systems has received great attention from robotics and control communities. In this paper, we investigate the distributed formation tracking problem in heterogeneous nonlinear multi-UAV networks via beari... Read More about Distributed Collision-Free Bearing Coordination of Multi-UAV Systems With Actuator Faults and Time Delays.

Swarm flocking using optimisation for a self-organised collective motion (2024)
Journal Article
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

Collective motion, often called flocking, is a prevalent behaviour observed in nature wherein large groups of organisms move cohesively, guided by simple local interactions, as exemplified by bird flocks and fish schools. Inspired by those intelligen... Read More about Swarm flocking using optimisation for a self-organised collective motion.

Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems (2023)
Presentation / Conference Contribution
Wu, K., Hu, J., Ding, Z., & Arvin, F. (2023). Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems. In H. Ishii, Y. Ebihara, J. Imura, & M. Yamakita (Eds.), 22nd IFAC World Congress (3447-3452). https://doi.org/10.1016/j.ifacol.2023.10.1496

This paper addresses the bearing-only formation tracking problem for heterogeneous nonlinear multi-robot systems. In contrast to position and distance-based formation algorithms, the robots can only measure the bearing information from their neighbor... Read More about Distributed Bearing-Only Formation Control for Heterogeneous Nonlinear Multi-Robot Systems.

Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring (2023)
Journal Article
Rajewicz, W., Wu, C., Romano, D., Campo, A., Arvin, F., Casson, A. J., …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

Rapidly intensifying global warming and water pollution calls for more efficient and continuous environmental monitoring methods. Biohybrid systems connect mechatronic components to living organisms and this approach can be used to extract data from... Read More about Organisms as sensors in biohybrid entities as a novel tool for in-field aquatic monitoring.

Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs (2023)
Journal Article
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

Area coverage is an important problem in robotics applications, which has been widely used in search and rescue, offshore industrial inspection, and smart agriculture. This paper demonstrates a novel unified robust path planning, optimal trajectory g... Read More about Unified Robust Path Planning and Optimal Trajectory Generation for Efficient 3D Area Coverage of Quadrotor UAVs.

Reinforcement learning-based aggregation for robot swarms (2023)
Journal Article
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

Aggregation, the gathering of individuals into a single group as observed in animals such as birds, bees, and amoeba, is known to provide protection against predators or resistance to adverse environmental conditions for the whole. Cue-based aggregat... Read More about Reinforcement learning-based aggregation for robot swarms.

Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements (2023)
Journal Article
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

This paper addresses a bearing-only formation tracking problem in robotic networks by considering exogenous disturbances and actuator faults. In contrast to traditional position-based coordination strategies, the bearing-only coordinated movements of... Read More about Finite-Time Fault-Tolerant Formation Control for Distributed Multi-Vehicle Networks With Bearing Measurements.

Federated Reinforcement Learning for Collective Navigation of Robotic Swarms (2023)
Journal Article
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

The recent advancement of Deep Reinforcement Learning (DRL) contributed to robotics by allowing automatic controller design. The automatic controller design is a crucial approach for designing swarm robotic systems, which require more complex control... Read More about Federated Reinforcement Learning for Collective Navigation of Robotic Swarms.

Cooperative Adaptive Cruise Control for Connected Autonomous Vehicles using Spring Damping Energy Model (2022)
Journal Article
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

A Novel Time-of-Flight Range and Bearing Sensor System for Micro Air Vehicle Swarms (2022)
Book Chapter
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

Optimization of a Self-organized Collective Motion in a Robotic Swarm (2022)
Book Chapter
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

Design and Experimental Validation of Deep Reinforcement Learning-Based Fast Trajectory Planning and Control for Mobile Robot in Unknown Environment (2022)
Journal Article
Chai, R., Niu, H., Carrasco, J., Arvin, F., Yin, H., & Lennox, B. (2022). 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, https://doi.org/10.1109/tnnls.2022.3209154

Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements (2022)
Presentation / Conference Contribution
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

Inspired by natural swarm collective behaviors such as colonies of bees and schools of fish, coordination strategies in swarm robotics have received significant attention in recent years. In this paper, a mixed formation control design based on edge... Read More about Mixed Controller Design for Multi-Vehicle Formation Based on Edge and Bearing Measurements.

Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field (2022)
Journal Article
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

Autonomous driving of multi-lane vehicle platoons have attracted significant attention in recent years due to their potential to enhance the traffic-carrying capacity of the roads and produce better safety for drivers and passengers. This paper propo... Read More about Distributed Motion Planning for Safe Autonomous Vehicle Overtaking via Artificial Potential Field.