Receding Path Planning for UAV Swarms Using Priority-based Artificial Potential Field

摘要

This paper presents a receding path planning method using priority-based artificial potential field (PAPF) for UAV swarms considering moving obstacle and inter-UAV collision avoidance constraint. To enhance computational efficiency, PAPF is proposed to decouple the UAV swarm cooperative path planning problem into a series of single-UAV path planning problems. The receding planning mechanism is used to reduce the horizon of the path planning to further reduce the computational burden. In each planning horizon, when sequentially generating the paths of multiple UAVs, lower priority UAVs treat the path points of higher priority ones as obstacles for collision avoidance. Simulation studies show that PAPF can generally generate swarm paths in around Is on the scenario involving 16 UAVs, which verifies the efficiency merit of PAPF in solving dynamic path planning problems for UAV swarms.