Collision Avoidance for Cooperative UAVs With Optimized Artificial Potential Field Algorithm

Abstract

Unmanned aerial vehicle (UAV) systems are one of the most rapidly developing, highest level and most practical applied unmanned aerial systems. Collision avoidance and trajectory planning are the core areas of any UAV system. However, there are theoretical and practical problems associated with the existing methods. To manage these problems, this paper presents an optimized artificial potential field (APF) algorithm for multi-UAV operation in 3-D dynamic space. The classic APF algorithm is restricted to single UAV trajectory planning and usually fails to guarantee the avoidance of collisions. To overcome this challenge, a method is proposed with a distance factor and jump strategy to solve common problems, such as unreachable targets, and ensure that the UAV will not collide with any obstacles. The method considers the UAV companions as dynamic obstacles to realize collaborative trajectory planning. Furthermore, the jitter problem is solved using the dynamic step adjustment method. Several resolution scenarios are illustrated. The method has been validated in quantitative test simulation models and satisfactory results were obtained in a simulated urban environment.