UAV Cluster Obstacle Avoidance Method Based on Improved Artificial Potential Field Method
Xinglong Gu, Guifen Chen, Yiming Sun · 2023
This paper presents an enhanced UAV cluster obstacle avoidance method that builds upon the artificial potential field (APF) approach. To address the challenges encountered during obstacle avoidance, several improvements are proposed. Firstly, a gravitational field based on dynamic target points is introduced to eliminate UAV oscillations. Additionally, a repulsive field is designed to effectively navigate through dynamic and static obstacles, utilizing the three-dimensional space efficiently. Secondly, a communication topology optimization strategy is proposed to adapt to rapid changes in UAV relative positions. Simulation results demonstrate the effectiveness of the proposed method, showcasing significant performance improvements over the traditional APF method in terms of obstacle avoidance, convergence, and overall efficiency of the UAV cluster.