UAV Swarm Real-Time Path Planning Algorithm Based on Improved Artificial Potential Field Method

Abstract

AbstractIn this paper, a novel real-time path planning algorithm for the unmanned aerial vehicle (UAV) swarm, based on improved artificial potential field method (APFM), is proposed to solve the issue that the traditional path planning method for a single UAV is not suitable for distributed UAV swarm. In this algorithm, UAV is not only subjected to the typical attraction of the target and repulsion of the obstacle in APFM but also to other forces. The attraction among UAV swarm is imported to keep the UAV swarm formation relatively compact, and the repulsion among UAV swarm is imported to prevent collisions between them, and the repulsion by the new obstacle is imported to solve the problem of incomplete reconnaissance obstacle outside the defense area. This method inherits APFM’s advantages, such as fast calculation speed, high real-time performance, and small memory occupation. The simulation results show the local extremum problem of a single UAV subjected to the attraction equal to the repulsion in APFM is solved. UAV swarm can reach their targets in tight formation. They can well avoid obstacles and new obstacles, and avoid collision among UAV swarm. All those verify the effectiveness of the algorithm.KeywordsUAV swarmDistributed systemReal-time path planningFormation constraintImproved APFM