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改进蚁群算法求解移动机器人路径规划问题

发表时间:2017-11-30  浏览量:888  下载量:120
全部作者: 王松杰,张永强,王连清
作者单位: 河北工程大学信息与电气工程学院;国防科技大学信息通信学院
摘 要: 提出基于改进蚁群算法的移动机器人全局路径规划方法。由于传统的蚁群算法收敛速度慢,容易陷入局部最优,引入局部启发式函数可以使算法的收敛速度得到极大提高。在信息素更新方面,仅更新相对路径较短的部分路径上的信息素,并根据局部路径信息对信息量进行动态调整,解决了信息素过度集中的问题。在保证算法收敛速度及算法寻优能力的同时,避免出现早熟现象。通过仿真实验得到了改进蚁群算法的最佳参数组合。最后,通过仿真实验证明了采用改进蚁群算法进行移动机器人的路径规划可使运行效率得到极大提高。
关 键 词: 算法理论;移动机器人;改进蚁群算法;路径规划;局部启发式函数
Title: Improved ant colony algorithm for solving path planning problem of mobile robot
Author: WANG Songjie, ZHANG Yongqiang, WANG Lianqing
Organization: School of Information and Electrical Engineering, Hebei University of Engineering; Department of Information and Communication, National University of Defense Technology
Abstract: Based on the improved ant colony algorithm, the global path planning for mobile robot is proposed. The traditional ant colony algorithm not only has the deficiency of slow convergence speed, but also tends to fall into local optimum solution. The design of local heuristic function in this paper can greatly increase the convergence speed. When it comes to pheromone update, the paper just updates the pheromone in the relatively shorter part of path, and carries on the dynamic adjustment for the amount of information based on local path information to solve the problems in concentration of pheromones. It not only guarantees that the convergence rate of the algorithm is constant, but also ensures the optimization ability of the algorithm and avoids premature phenomenon at the same time. The best parameter combination of the improved ant colony algorithm can be gained by conducting the simulation experiment. In the end, it is proved that the efficiency of the path planning in this paper is improved greatly.
Key words: algorithm theory; mobile robot; improved ant colony algorithm; path planning; local heuristic function
发表期数: 2017年11月第22期
引用格式: 王松杰,张永强,王连清. 改进蚁群算法求解移动机器人路径规划问题[J]. 中国科技论文在线精品论文,2017,10(22):2452-2458.
 
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