All Outputs (6)

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.

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 ⋆.

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.

A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments (2024)
Presentation / Conference Contribution
Sun, H., Hu, J., Dai, L., & Chen, B. (2024, August). A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments. Presented at 2024 IEEE International Conference on Automation Science and Engineering (CASE), Bari, Italy

Safety-guaranteed trajectories are important for multi-agent systems to work in an unknown constrained environment. To address this issue, this paper proposes a cooperative path planning strategy for a swarm of agents such that they can achieve a tar... Read More about A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments.

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.

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.