An APF path planning method for multi-agent systems under butterfly algorithm optimization

This paper proposes a solution for multi-agent path planning in complex environments, addressing issues like inefficient obstacle avoidance, path roughness, and adaptability challenges. The approach combines a leader-follower strategy with an optimized artificial potential field method using the butterfly algorithm. Enhancements include dynamic coefficient adjustments in the possible field method to escape local optima and an objective function integrating path smoothness, length, and obstacle avoidance for the leader robot. The butterfly algorithm optimizes this function to refine the path planning, aiming to enhance overall performance.