UAV Path Planning Based on Expert Experience Strategy RRT Algorithm
Hengzhuang Zhang, Mingming Wang, Yuan Ping, Chong Wu, Juntong Qi, Wenyue Wu, Enkui Zhou · 2024
In response to the issues of node blind expansion, excessive nodes, and frequent acceleration of UAV swarms during path planning using the RRT algorithm, this paper proposes a novel RRT algorithm based on expert experience (E-RRT), Considering the safety and effectiveness of the UAV swarm and its path planning, a strategy involving single UAV reconnaissance and UAV swarm follow-up is adopted. The E-RRT algorithm comprises the following key components: Firstly, an endpoint-guided strategy is devised for the reconnaissance single UAV, introducing a local expansion approach guided by the endpoint to overcome the issue of node blind expansion. After ensuring the reconnaissance single UAV’s safety through the reconnaissance path, an expert-based node selection strategy is employed to generate an optimized path for the subsequent UAV swarm follow-up. To enhance the smoothness of the path, a cubic B-spline curve fitting technique is applied to the path generated. Finally, simulations are conducted using Matlab software and the Cyber UAV platform to validate the effectiveness and superiority of the proposed algorithm in UAV swarm path planning.