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 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.