Obstacle Avoidance Control for Multiagent Systems Based on Model-Free Adaptive Control

This article addresses the problem of collision avoidance and obstacle avoidance in nonlinear multiagent control using a data-driven cooperative output approach. First, to avoid collisions with obstacles, a safe reference trajectory planning method is proposed, which dynamically projects unsafe segments of a reference trajectory onto the outer boundary of obstacle regions, enabling the agent to bypass the obstacle. Second, by using only input-output information, a distributed tracking controller incorporating two dynamical barrier functions is designed, which allows the agent to adaptively decelerate within the coverage range of the barrier function to avoid collisions. Finally, sufficient conditions are provided to ensure that the agent can successfully bypass obstacles using the proposed control strategy. Simulation results confirm that the proposed method enables the agent formation to timely avoid stationary/moving obstacles, prevent collisions between agents, and effectively track the desired trajectory while maintaining formation.