Mobile Robot Path Planning Algorithm Based on Rapidly-Exploring Random Tree

Abstract

A path planning algorithm is proposed for the problems of high node randomness and repeatability using the Rapidly-exploring Random Tree (RRT) algorithm in the path planning. Firstly, the method of region division centered on newly generated nodes is proposed to reduce randomness, the generation rules of temporary target nodes are guided to reduce repetitiveness, then improve the efficiency of path planning through adaptive step size strategy, smooth the planned path to improve the length of the path in the end. Simulation results show that the improved RRT algorithm can effectively plan the path for mobile robots.