Research for the Robot Path Planning Control Strategy Based on the Immune Particle Swarm Optimization Algorithm

Abstract

In order to improve robot path search ability in unknown environment, avoid obstacle to reach the destination quickly, IPSO algorithm is proposed for path planning. The robot two-dimensional space model is established by MAKLINK, obtains the shortest-path through the Dijkstra algorithm, uses the Particle Swarm algorithm crossover and mutation operators to optimize this path. Compared with Dijkstra optimization results and PSO optimization results, the control performance of the robot path and the execution time are increased separately by 6.07%, 5.10% and 21.35%, 20.27% through IPSO strategy. The simulation result indicates the robot path planning's IPSO control quality surpasses other two methods', the convergence rate, the search accuracy and robustness of time-varying parameters is raised obviously, while PSO's "premature" problem is avoided.