Sun, Hao;
Hu, Junyan;
Dai, Li;
Chen, Boli;
(2024)
A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments.
In:
Proceedings of the 20th International Conference on Automation Science and Engineering 2024.
Institute of Electrical and Electronics Engineers (IEEE)
(In press).
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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.
Type: | Proceedings paper |
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Title: | A Multi-Agent Path Planning Strategy with Reconfigurable Topology in Unknown Environments |
Event: | 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE 2024) |
Location: | Bari, Italy |
Dates: | 28th August - 1st September 2024 |
Open access status: | An open access version is available from UCL Discovery |
Publisher version: | https://ieeexplore.ieee.org/Xplore/home.jsp |
Language: | English |
Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng |
URI: | https://discovery.ucl.ac.uk/id/eprint/10193053 |
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