A Differential Game Approach to Collision Avoidance in Multi-Agent Systems

This paper gives a novel differential game scheme to solve the collision avoidance problem for multi-agent systems. Based on the concept of artificial potential field (APF), we combine obstacle avoidance objectives with trajectory optimization targets as the performance index. The feedback strategie...

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Bibliographic Details
Published in2022 41st Chinese Control Conference (CCC) pp. 1785 - 1790
Main Authors Xue, Wenyan, Wu, Zhihong, Zhan, Siyuan, Chen, Yutao, Huang, Jie
Format Conference Proceeding
LanguageEnglish
Published Technical Committee on Control Theory, Chinese Association of Automation 25.07.2022
Subjects
Collision avoidance
differential game
Differential games
Nash equilibrium
Performance analysis
Riccati equations
Simulation
Trajectory optimization
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Summary:This paper gives a novel differential game scheme to solve the collision avoidance problem for multi-agent systems. Based on the concept of artificial potential field (APF), we combine obstacle avoidance objectives with trajectory optimization targets as the performance index. The feedback strategies are based on the solutions of coupled Riccati equations. Furthermore, it is proved that the feedback strategies will converge to a Nash equilibrium (NE). Finally, simulation results are provided to show the advantages, which make agents arrive at the targeted position collision-free with a reduced time.
ISSN:2161-2927
DOI:10.23919/CCC55666.2022.9902673