An Improved Path Planning for Mobile Robots

Abstract

Path planning is one of the most important technologies in navigating mobile robot. Which finds an optimal path to reach the destination within the shortest possible time. Based on the Rapidly-exploring Random Tree (RRT) and Particle Swarm Optimizer (PSO), a path planning of the robot is proposed in this paper. The RRT which has strong global search capability algorithm is used to obtain the global navigation path, and the PSO algorithm which as strong local search capability is adopted to get a better path. Computer experiment results show that this novel algorithm can find an optimal path rapidly in short time. A successful obstacle avoidance is achieved, and the model is robust and performs reliably.