Particle Swarm Optimization Algorithm Based on Artificial Potential Field

摘要

Artificial potential field method is a simple and effective path planning algorithm. In this paper, the basic idea of artificial potential field method is inherited. The gravitational potential field and repulsive potential field are introduced into particle swarm optimization. The gravitational potential field is used to enhance the optimization of particles. The repulsive potential field is used to increase the search range of particles to prevent the particles from falling into the local excellent solution. This paper tests the function, experiments show that this method is effective.