车间环境下多AGV路径智能优化研究

Research on the Intelligent Optimization of the Pathway of Multiple AGVs in the Inter-Vehicle Environment

随着我国工业技术的高速发展,多自动运输车(Automated Guided Vehicle,AGV)在自主性和节约成本方面,受到越来越多的重视。基于多AGV在复杂多变的车间环境中的路径规划问题,提出了改进的A~*算法和DWA算法(Dynamic Window Approach)融合的智能优化算法。首先,利用A~*算法规划出从起点到终点的全局路径,然后针对A~*算法多冗余的缺点,提出了一种提取关键点的方法,剔除掉全局路径中的冗余节点和多余拐点,保证了对全局路径的改进。其次,通过对全局路径的分段,设置一系列的局部目标点,利用DWA动态窗口法对新增和移动的障碍物进行动态避障的同时不断到达局部目标点,得到了多AGV从起点到目标点的最优路径,最终实现了对多AGV关于路径长度和安全性方面的改进。

With the rapid development of industrial technology in China,the automated guided vehicle(AGV)is receiving increasing attention in terms of autonomy and cost saving.This article proposes an intelligent optimization algorithm that integrates the improved A*algorithm and DWA(dynamic window approach)for the path planning problem of multiple AGVs in the complex and variable inter-vehicle environment.Firstly,this article uses the A*al-gorithm to plan the global path from the starting point to the endpoint,and then,for the shortcoming of the mul-tiple redundancy of the A*algorithm,proposes a method for extracting key points to eliminate the redundant nodes and inflection points of the global path,which ensures the improvement of the global path.Secondly,by segment-ing the global path,it sets a series of local target points,and uses the DWA to dynamically avoid newly-added and moving obstacles while continuously reaching the local target points,so as to obtain the optimal path for multiple AGVs from the starting point to the target point,and ultimately achieve the improvement of the path length and safety of multiple AGVs.