An Improved Ant Colony Optimization Algorithm for Mobile Robot Path Planning

Juanping Zhao, Xiuhui Fu, Ying Jiang
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引用次数: 13

Abstract

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.
移动机器人路径规划的改进蚁群优化算法
采用蚁群双向并行搜索策略加快了搜索速度,但很明显该策略丢失了一些可行路径,甚至丢失了最优路径,因此本文提出了一种新的蚁群相遇判断方法。同时加入信息素增益,合理分配初始信息素,以解决初始信息素等价分配带来的搜索速度慢的问题。设计了信息素互导法,加快了优化速度。上述设计可以加快搜索速度,但可能使算法陷入局部最优,因此引入混沌干扰帮助算法跳出局部最优。仿真结果表明,在二维环境下,机器人的最优运动路径能够安全、快速地到达。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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