An Improved UAV Path Planning method Based on RRT-APF Hybrid strategy
Lu Yafei, Anping Wu, Chen Qingyang, Wang Yujie
Abstract
Autonomous path planning in complex environments is a hot topic for current UAV mission planning researchers, and there is usually no distinction between threats and obstacles. In order to solve the problem of unknown threat and obstacle characteristics in the existing algorithms, a UAV penetration path planning algorithm based on the artificial potential field and the RRT algorithm is proposed. The RRT algorithm makes it possible to distinguish between the characteristics of threats and obstacles in the penetrating algorithm. The problem of too strong randomness of RRT algorithm is solved by increasing the adaptive target gravity when the growth of nodes is guided to the target direction. The simulation results show that the algorithm can avoid the threat area quickly and effectively, and a better trajectory is obtained to meet the demand of UAV real-time path planning.