农机化研究Issue(9)：48-52,5.
基于改进蚁群算法的农业机器人路径规划研究
Research for the Path Planning of the Agricultural Robot Based on the Improved Ant Colony Algorithm
摘要
Abstract
In response to the problems of agricultural robot path planning bad real-time and stability,artificial potential field, elite sorting method combined with Memetic algorithm is adopted.This algorithm initialize the path population with potential field method,optimizes the sorting of each generation ants path.And also updates the pheromone according to the superiority of the ants path.At the same time, with the help of the pheromone of the elite ants, and using crossover and mutation operation of the memetic algorithm on each generation path,so as accelerate the convergence speed of the al-gorithm, improves the stability of it.The simulation results show that the improved algorithm of the optimal path length on average increased by 12 .56%,the convergence generation increased by 55 .86%, the algorithm time increased by 65 . 3%,and the optimal solution percentage increased by 40%,this shows that the mentioned algorithm can plan the optimal path in a quick and efficient way, improving the efficiency of agricultural robot.关键词
农业机器人/Memetic算法/路径规划/蚁群算法/精英排序/人工势场Key words
agricultural robot/memetic algorithm/path planning/ant colony algorithm/elite sorting/artificial potential field分类
农业科技引用本文复制引用
朱铁欣,董桂菊,颜丙学,郭凯敏,谢学刚,郭志强..基于改进蚁群算法的农业机器人路径规划研究[J].农机化研究,2016,(9):48-52,5.基金项目
国家“863计划”项目 （）
