Path Planning of Mobile Robot Based on Improved Ant Colony Algorithm

Abstract

In order to solve the problems of slow convergence and easy falling into local optimization in path planning of mobile robot, an improved ant colony algorithm is proposed. The improved algorithm can enhance the performance of path planning from three aspects. Firstly, based on the environmental information, the obstacle avoidance factor and heuristic function are introduced to improve the searching efficiency at early-stage; Secondly, a high-quality ant pheromone updating rule is suggested to enhance the algorithm's convergence speed; Finally, based on the searched path, a self-adaptive pheromone evaporation factor is used to improve the global searching capability. In two different experimental environments, the improved colony algorithm have better performance in path length and convergence speed than other algorithm.