An Improved B-RRT* Method for UAV Path Planning
Abstract— With the fast development of science and technology, unmanned aerial vehicle (UAV) becomes more popular. As the use range of UAV expanding from the military to the civilian field, its path planning problem attracts lots of attentions. The conventional B-RRT* algorithm can not obtain the direct route for UAV flight. In this paper, an improved B-RRT* algorithm is proposed. The proposed algorithm is combined the dynamics constraints of the UAV with the node expansion of the extended tree. It firstly adopt to the backward fan-shaped area sampling method to improve the convergence speed from the selection strategy of random points. Then an adaptive step size is used to overcome the shortcomings of the limitations of growth at the adjacent of obstacles. Simulation results show that the proposed algorithm has a shorter path planning length with stronger stability, compared with other competing path planning method.
Index Terms— path planning, dynamic constraint, backward fan-shaped area sampling, adaptive step size. 1. Introduction With the progress of electronic information technology and the devel
Shuai Zhao, Zhiyuan Shen, Wenbin Wei
College of Civil Aviation, Nanjing University of Aeronautics and Astronautics, CHINA
Cite: Shuai Zhao, Zhiyuan Shen, Wenbin Wei, "An Improved B-RRT* Method for UAV Path Planning," Proceedings of 2018 the 8th International Workshop on Computer Science and Engineering, pp. 14-18, Bangkok, 28-30 June, 2018.