Catalina Agachi
RRT*-Based Leader-Follower Trajectory Planning and Tracking in Multi-Agent Systems
Agachi, Catalina; Arvin, Farshad; Hu, Junyan
Authors
Professor Farshad Arvin farshad.arvin@durham.ac.uk
Professor
Dr Junyan Hu junyan.hu@durham.ac.uk
Assistant Professor
Abstract
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, this research presents a novel method for multi-agent systems to navigate through environments with obstacles. The system consists of a group of agents with a leader-follower structure, where the leader aids in guiding the agents toward the target location and the followers are steered to maintain a flexible formation. To achieve cooperation, the agents communicate within a connected and undirected network, exchanging information within a specific radius. The leader's path is generated using the RRT* algorithm, which serves as a reference for the followers. A control law utilizes consensus and APF is then implemented, ensuring coordinated motion while maintaining safe distances among agents and between agents and obstacles. Finally, the effectiveness of the developed two-layer coordination strategy is verified by simulations.
Citation
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
Presentation Conference Type | Conference Paper (published) |
---|---|
Conference Name | 2024 IEEE International Conference on Intelligent Systems (IS) |
Start Date | Aug 29, 2024 |
End Date | Aug 31, 2024 |
Acceptance Date | Jun 11, 2024 |
Deposit Date | Aug 9, 2024 |
Peer Reviewed | Peer Reviewed |
Book Title | 2024 IEEE International Conference on Intelligent Systems (IS) |
Keywords | Path planning; cooperative control; multi-robot systems; swarm robotics |
Public URL | https://durham-repository.worktribe.com/output/2745359 |
Publisher URL | https://ieeexplore.ieee.org/xpl/conhome/1000395/all-proceedings |
This file is under embargo due to copyright reasons.
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