Manipulator Motion Planning Based on Improved RRT Algorithm

Abstract

Aiming at the problems that the Rapidly-exploring Random Tree (RRT) algorithm has more time-consuming and longer paths in the manipulator motion planning, we propose an improved RRT algorithm based on probabilistic target bias strategy and triangular inequality pruning method. This paper simulates the algorithm from three dynamic environments with different numbers of obstacles. The simulation results show that the proposed improved RRT algorithm can plan a shorter path in less time.