Path Planning of Multipoint Region Attraction RRT* Algorithm in Complex Environment

In recent years, Rapidly-exploring Random Trees, as a fast searching method, has been widely studied in the field of path planning, while RRT* algorithm, as an improved RRTs algorithm, has attracted much attention because it can realize the progressive optimal solution of path planning. However, there are still some problems to be solved, such as low convergence rate, low path utilization rate and unsmooth path. In this paper, a multipoint region attraction RRT* (Mra-RRT*) algorithm is proposed to solve the above problems. Firstly, the convergence rate is accelerated by using the multipoint region attraction strategy. Secondly, the path storage function is realized in this paper. Before generating the new path, it is possible to query and call part of the stored path, which greatly improves the path utilization and search time efficiency. Finally, the path smooth processing is sovled by using cubic spline interpolation, which makes the change of path points more gentle and easy to apply to the actual situation. Simulation results show that the algorithm is effective in two-dimensional and three-dimensional complex obstacle spaces.