Simulation Research on Path Planning of Mobile Robot

Abstract

Mobile robot path planning problem is studied.Conventional mobile robot path planning algorithms have problems such as long searching time and low efficiency.This paper puts forward a robot path planning method based on particle swarm optimization algorithm(PSO).This method firstly uses neural network to build robot's working environment and establishes new map based on transformation,then the path is represented by particle position,and path length is used as particle swarm of fitness value.Finally the particle position and velocity are updated by the cooperation between particles,and obtains an optimal path from starting point to target.Simulation experiment is carried out with MATLAB,and the experimental results show that the robot path planning method based on PSO improves the computational efficiency and reliability of path planning,and it can be applied to the real-time navigation robot.