A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments

Sun, Hao; Hu, Junyan; Dai, Li; Chen, Boli

Abstract

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 target formation and handle unknown obstacles during complex tasks. By considering the sensing range and agent dimension, a group of artificial potential field functions are designed aiming at enabling agents reconfiguration (e.g., split and merge) for reinforced flexibility. A distributed path planning scheme is then developed to achieve formation tracking while avoiding any potential collisions. Theoretical analysis using the Lyapunov theory is given to guarantee the performance of the system. Finally, numerical simulations are carried out to verify the effectiveness of the proposed algorithm and its superiority against conventional methods.

Citation

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

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 2024 IEEE International Conference on Automation Science and Engineering (CASE)
• Start Date: Aug 28, 2024
• End Date: Sep 1, 2024
• Acceptance Date: Jun 3, 2024
• Online Publication Date: Oct 23, 2024
• Publication Date: Oct 23, 2024
• Deposit Date: Aug 9, 2024
• Publicly Available Date: Oct 23, 2024
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Pages: 2223-2228
• Series ISSN: 2161-8070
• Book Title: 2024 IEEE International Conference on Automation Science and Engineering (CASE)
• DOI: https://doi.org/10.1109/CASE59546.2024.10711600
• Public URL: https://durham-repository.worktribe.com/output/2745370