节点文献
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】 针对农业机器人路径规划实时性和稳定性差的问题,采用人工势场法,并结合Memetic算法与精英排序法优化基本蚁群算法。该算法用势场法获得路径初始化种群,对每代路径进行Memetic算法中的交叉组合操作,将每代蚂蚁产生的路径分别进行优化排序,根据蚂蚁路径的优劣程度,对信息素进行更新;同时,加入精英小组蚂蚁产生的信息素,从而加快了算法的收敛速度,提高了算法的稳定性。实验表明:改进后算法的平均最优路径长度提高了12.56%,收敛代数提高55.86%,算法用时提高了65.3%,最优解百分比增加了40%。本算法能够快速有效地规划出最优路径,提高了农业机器人的工作效率。
【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 algorithm,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.
【Key words】 agricultural robot; memetic algorithm; path planning; ant colony algorithm; elite sorting; artificial potential field;
- 【文献出处】 农机化研究 ,Journal of Agricultural Mechanization Research , 编辑部邮箱 ,2016年09期
- 【分类号】TP18;TP242
- 【被引频次】32
- 【下载频次】481