基于改进A^(*)算法的仓储AGV路径规划  

Warehouse AGV path planning based on improved A^(*)algorithm

作　　者：秦浩然 刘明 QIN Haoran;LIU Ming(School of Electrical and Information Technology,Yunnan Minzu University,Kunming 650031,China)

机构地区：[1]云南民族大学电气信息工程学院,云南昆明650031

出　　处：《电子设计工程》2023年第9期49-53,58,共6页Electronic Design Engineering

摘　　要：针对仓储环境下A^(*)算法在自动导引车(Automated Guided Vehicle,AGV)路径规划中拓展节点速度较慢、搜索效率低、生成路径曲折的问题,采用了动态加权系数和引入转弯惩罚的方法,对A^(*)算法中代价函数的实际累积代价和估计代价分别加权,平衡累积代价和估计代价对算法搜索速度的影响,构造与AGV能耗相关联的惩罚项,减少路径转折点数量,提高系统工作效率。结合Matlab软件仿真试验,得出相比传统A^(*)算法,改进算法经动态加权,搜索时间平均缩短了11.8%,引入转弯惩罚后,转弯角度平均缩短了66.1%,生成的路径质量更高。Aiming at the problems of slow expansion node,low search efficiency and tortuous path generation of A^(*)algorithm in Automatic Guided Vehicle(AGV)path planning in warehousing environment,the dynamic weighting coefficient and the method of introducing turning penalty are adopted to weight the actual cumulative cost and estimated cost of the cost function in the A^(*)algorithm respectively,balance the influence of cumulative cost and estimated cost on the search speed of the algorithm,and construct the penalty item associated with AGV energy consumption.Reduce the number of path inflections and improve system efficiency.Combined with the Matlab software simulation experiment,it is concluded that compared with the traditional A^(*)algorithm,the improved algorithm is dynamically weighted,the search time is shortened by 11.8%on average,and the turning angle is shortened by 66.1%on average after the introduction of the turning penalty,and the generated path quality is higher.

关 键 词：A^(*)算法 启发函数 自动导引小车 路径规划 

分 类 号：TN96[电子电信—信号与信息处理]