An Improved RRT<sup>*</sup> UAV Formation Path Planning Algorithm Based on Goal Bias and Node Rejection Strategy
Haiying Liu, Jie Chen, Jianxin Feng, Haiping Zhao
Abstract
This paper proposes an improved RRT * formation path planning algorithm based on goal bias and node rejection strategy to solve UAVs’ formation path planning problems in a complex environment. Aiming at the position constraint problem of multi-UAV in the planning process, the leader–follower structure among UAVs and the formation configuration model are established. Furthermore, aiming at node redundancy and slow planning speed caused by the RRT * algorithm in a complex environment, this paper sets the goal bias information so that the random tree could find the initial path quickly. At the same time, this paper proposes a node rejection strategy to prevent the nodes that do not meet the pre-set conditions from participating in the subsequent expansion. Compared to the standard RRT-related algorithms, the proposed improved algorithm can shorten the planning time, reduce the number of algorithm iterations and improve the algorithm’s applicability in the formation path planning problem.