Research on Path Optimization with PSO for Unmanned Vehicle

Li Cai,Juan Lei,Jianping Jia

doi:10.3991/ijoe.v11i8.4878

Abstract

The development of autonomous unmanned vehicles is of high interest to many organizations around the world and path planning is the key point of the navigation for the autonomous unmanned vehicle. Intelligent algorithms have been applied in this field and an essential aspect of unmanned vehicles autonomy is the ability for automatic path planning. In this paper, particle swarm optimization algorithm as one of new swarm intelligent optimization methods is introduced into a path planning for autonomous vehicle, which is constructed of a particle representation methods for vehicle routing problem with fast convergence speed. The results show that the particle swarm optimization algorithm can obtain the solution of the vehicle routing problem quickly and effectively. It is a good method for solving the vehicle routing problem.

Highlights

The route planning problem is a key element of the unmanned aerial vehicle autonomous control module
The results show that the particle swarm optimization algorithm can obtain the solution of the vehicle routing problem quickly and effectively
It can be seen that Particle swarm optimization (PSO) algorithm is acceptable to solve routing problem, which has flexibility and collaboration features

Summary

INTRODUCTION

The route planning problem is a key element of the unmanned aerial vehicle autonomous control module. In order to take the motion constraints of unmanned aerial vehicle into account during the planning process, some new algorithms were proposed. In view of improving the limitations, this paper proposes a path planning for autonomous vehicle based on particle swarm optimization algorithm. PSO algorithm for path planning is introduced and the simulation results through the comparison of two kinds of optimization algorithm in the MATLAB software show that the method of introducing PSO into autonomous vehicle is convenient. By this means, the path planning is well optimized in real-time way for vehicle routing problem. IJOE ‒ Volume 11, Issue 8, 2015: "Online Engineering Innovations based on Intelligent Information Processing" 21

AUTONOMOUS VEHICLE MODEL

THE PRINCIPLE OF PSO ALGORITHM

SIMULATION OF PSO ALGORITHM

CONCLUSION