机器人空间路径规划的ACO算法特性分析

ACO Algorithm Characteristic Analysis of Robot's Space Path Planning

为进一步研究机器人的移动空间路径规划方法,分析蚁群算法的主要系数对路径规划的影响,根据蚁群优化算法的主要特点,对机器人的移动空间信息采用栅格法进行全局描述。对蚁群优化算法的主要系数如蚁群数量m和信息素蒸发系数ρ等进行选择,以路径长度和迭代次数为目标,仿真分析其对规划路径的长度和路径规划效率的影响,找到最佳匹配系数组。仿真结果表明:合理选择算法系数能够缩短机器人的移动空间路径规划长度,且能提高路径规划效率。

In order to further research the path planning method of robot＇s mobile space and analyze the influence of main coefficients of ant colony algorithm on path planning, the mobile spatial information of the robot is described by the grid method according to the main characteristics of ant colony optimization algorithm. With the path length and the number of iterations as the goal, the key parameters such as the number of ant colony and information pheromone evaporation coefficients of the ant colony optimization algorithm are selected to simulate and analyze their influence on the length and efficiency of the path planning to get the best array of path. The simulation results show that the reasonable selection of algorithm parameters can achieve the short path planning length of the robot＇s mobile space and the high path planning efficiency.