Enhanced Ant Colony Optimization Algorithm for Global Path Planning of Mobile Robots

Abstract

An enhanced ant colony optimization algorithm is proposed. The search deadlock is ruled out through modifying both initial environment pheromone and state transition probability. The roundabout of trajectory is improved by combining deterministic search with stochastic search. Experimental results show that the new algorithm can provide desirable safety path under the complex situation, which contains dense obstacles or many concave blocks, as well as computational time can meet the requirement of practically applications.