摘要
随着自动导引车(Automated Guided Vehicle,AGV)在仓储物流等领域的普及,AGV路径规划问题成为近年来国内外学者研究的热点。针对传统A^(*)算法存在的转向多、效率慢等问题,提出一种基于启发函数的改进A^(*)算法。该算法通过优化扩展规则,以引入转弯修正参数的加权曼哈顿距离为启发函数,减少转向;优化管理遍历节点数,提高算法计算效率。经过MATLAB仿真实验对比表明,改进A^(*)算法能显著降低转弯频率和遍历节点的数量,同时提升路径寻找效率和路径流畅性。
With the popularization of Automated Guided Vehicles(AGV)in logistics and warehousing and other fields,the AGV path planning problem has become a hotspot for scholars at home and abroad in recent years.In this paper,regarding the traditional A^(*)algorithm,which has the problems of many turns and slow efficiency,we propose an A^(*)algorithm that improves the heuristic function.The algorithm reduces steering by optimizing the expansion rule;adopting the weighted Manhattan distance,which introduces the turn correction parameter,as the heuristic function;and optimizing the number of management traversal nodes to improve the algorithm's computational efficiency.After MATLAB simulation experiments and comparisons show that the improved A^(*)algorithm can significantly reduce the turning frequency and the number of traversal nodes,and at the same time improve the path finding efficiency and path fluency.
作者
刘亚宁
张东升
LIU Yaning;ZHANG Dongsheng(School of Engineering Machinery,Shandong Jiaotong University,Jinan Shandong 250357,China)
出处
《信息与电脑》
2023年第23期62-65,共4页
Information & Computer
