摘要
依据蚁群算法的特点,对移动机器人的全局路径规划方法进行了研究。采用栅格法描述移动机器人的环境信息,仿真分析了蚁群算法的主要参数如蚁群数量m、启发因子α、期望启发因子β和信息素挥发系数ρ等对规划路径的长度和路径规划效率的影响。研究结果表明,当算法的参数匹配时,获得的规划路径不仅长度短,且路径规划效率高。通过仿真找到了最佳匹配参数组。基于仿真结果,对工作在不同环境下的移动机器人进行了全局路径规划仿真实验,研究结果验证了蚁群算法最佳匹配参数组的准确性。
The global path-planning method for MR is studied based on the characteristics of ant colony algorithm. The environment information of a plane on which mobile robot （MR） works is expressed by the grid method. The main parameters used by ant colony algorithm, such as the number of ant m, arouse factor a , expected arouse factor 13 and information element hangover coefficients p, which affect the result of path planned, including the length of the path planned and the efficiency planning path, are simulated. It is found from the simulation result that the better global path can be gotten. The length of the path planned is shorter and the efficiency of planning path is higher when the parameters m, α/β and ρ are matched better. Based on the results of above simulation, the path is planned for MR, which works on two different work-plane using ant colony algorithm with the best matching parameters obtained from the simulation. The accuracy of theoretical research is verified by the global path planned for MR working under the different work-plane.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2014年第6期53-57,共5页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家科技重大专项资助项目(2009ZX04014)
关键词
移动机器人
蚁群算法
路径规划
参数匹配
Mobile robot Ant-colony algorithm Work path planning Matching parameters
作者简介
史恩秀，副教授，博士，主要从事智能移动机器人运动控制与导航技术研究，E—mail：shienxiu@163．com
