Path planning for mobile robot using the particle swarm optimization with mutation operator

Abstract

Path planning is one of the most important technologies in the navigation of the mobile robot, which should meet the optimization and real-time requests. This paper presents a novel approach of path planning. First the MAKLINK graph is built to describe the working space of the mobile robot; then the Dijkstra algorithm is used to obtain the shortest path from the start point to the goal point in the graph, finally the particle swarm optimization algorithm is adopted to get the optimal path. Aiming at the shortcoming of the PSO algorithm, that is, easily plunging into the local minimum, this paper puts forward an advanced PSO algorithm with the mutation operator. By adding a mutation operator to the algorithm, it can not only escape the attraction of the local minimum in the later convergence phase, but also maintain the characteristic of fast speed in the early phase. The results of the simulation demonstrate the effectiveness of the proposed method, which can meet the real-time requests of the mobile robot's navigation.