An Efficient and Improved Particle Swarm Optimization Algorithm for Swarm Robots System

Abstract

In recent years, the number of researches in which swarm intelligence shown by individual communication in swarm robots is increasing. As one of the representative algorithms in swarm intelligence, particle swarm optimization has been applied to many fields because of its simple concept, easy realizing and good optimization characteristics. However, it still has some disadvantages such as easy falling in the local best situation and solving the discrete optimization problems poor. In this paper, genetic algorithm has been integrated with particle swarm optimization to improve the performance of the algorithm; the simple particle swarm optimization algorithm has been simulated in the Player/Stage and compared with the particle swarm optimization. The simulation shows that the algorithm is faster and more efficient. © Springer-Verlag Berlin Heidelberg 2013.