A distributed genetic algorithm for swarm robots obstacle avoidance

Abstract

Obstacle avoidance is an extremely important task in swarm robotics as it saves robots from hitting objects and being damaged. A Genetic algorithm can be used to teach robots how to avoid obstacles in different environments. However the evaluation module of this genetic algorithm can be very time consuming module as each candidate solution should be evaluated N times. This paper explains the methodology used to distribute the evaluation module of genetic Algorithm over a cluster of computers to speed up the algorithm. The proposed methodology can be used for any application which suffers from time consuming evaluation module. Experimental results showed that the speedup can reach 70x.