Obstacle Avoidance Path Planning of Manipulator Based on Improved RRT Algorithm
Yang Wen, Wen Haiying, Zhang Zhisheng · 2021
Rapidly-exploring Random Tree (RRT) algorithm is suitable for solving path planning problems under high-dimensional space and complex constraints. To solve the problem of the RRT algorithm such as strong randomness, path redundancy, an improved-RRT algorithm with target probability offset and variable step size control is proposed in this paper. The improved-RRT algorithm can improve the operation efficiency and optimize the path. The average planning time of the improved RRT algorithm is reduced by 70.05%. At the same time, the end effector of the manipulator can reach the target position and orientation and each joint will not collide with obstacles in space. The correctness and effectiveness of the proposed method are demonstrated and validated via a MATLAB simulation.