An Improved Ant Colony Optimization Algorithm for Mobile Robot Path Planning

摘要

Ant two-way parallel searching strategy is adopted to accelerate searching speed, but it is clearly seen that this tactic loses some feasible paths and even loses optimal path, so a new ants meeting judgment method is proposed in this paper. At the same time pheromone gain is added to allocate initial pheromone reasonably in order to deal with slow searching speed brought by equivalence distributing of initial pheromone. Pheromone mutual leading method is also designed to accelerate optimizing speed. Above designs can accelerate searching speed but maybe put algorithm running into local optima, so chaos disturbance is introduced to help algorithm jumping out local optima. Finally simulation results indicate that the optimal path on which the robot moves can reach safely and rapidly under 2-D environment.