Robot Path Planning based on Swarm Intelligence

Abstract

Robot path planning is a NP problem, traditional optimization methods are not solve it very well just like genetic algorithm, which are easy to trap into local optimal. Particle Swarm Optimization (PSO) algorithm was developed under the inspiration of behavior laws of bird flocks, fish schools and human communities, compared with genetic algorithm the PSO algorithm has high convergence speed. In this paper, aim at the disadvantages of standard PSO algorithm like being trapped easily into a local optimal, we improves the standard PSO and proposes a new algorithm to solve the overcomes of the standard PSO. The new algorithm keeps not only the fast convergence speed characteristic of PSO, but effectively improves the capability of global searching as well. Compared with genetic algorithm on the robot path planning problem, the results show that the new algorithm can get more accuracy path and the calculation time is faster.