RRT* path planning method for mobile robot based on particle swarm optimization and rotation angle constraint
Heran Zhuang, Chunying Jiang · 2025
Aiming at the problem of low efficiency and poor accuracy of Optimal Rapidly-Exploring Random Tree (RRT*) method in robot path planning, a RRT* path planning method for mobile robot based on particle swarm optimization and corner constraint is proposed(PSO-RRT*). In the path growth direction, a path direction probability selection method under target and obstacle constraints is proposed to reduce the path search time. In the process of path exploration, taking the current node as the starting point, through multiple forward explorations, combined with the minimum rotation angle constraint of the robot, a local path under multiple rotation angle constraints is established. Using the particle swarm optimization method, the current multiple paths are selected to obtain the optimal local path, and the redundant nodes in the path are deleted. Finally, the B-spline curve is used to smooth the final path, and the predictive control method is used to track the path. The simulation and experimental results show that compared with the other methods, the average planning time of the proposed method is shortened by about 10%, the path length is reduced by 10%, and the smoothness is better, which shows that the proposed method has certain engineering practical value.