基于改进A*算法的仓库物料车路径规划

Improved A*Algorithm-based Path Planning for Warehouse Material Trucks

生产实践证明,高效率的企业生产离不开生产物流的支持。仓库内的物料配送是生产物流系统的重要组成部分,由于仓库内部复杂的障碍环境,往往难以合理规划其配送路线。如果能够合理规划仓库内的配送路线,就可以提高配送环节的效率,有助于提高生产效率。以改进的A*算法在仓库物料配送路径规划中的应用为研究对象,首先分析仓库物料配送路径规划的环境,其次采用栅格法模拟仓库下的环境,完成对障碍物环境下的配送仿真实验。分析A*算法的搜索原理,并通过融合改进的A*算法与动态窗口(Dynamic window approach,DWA)算法,设计融合算法,改进后的融合算法将具有更优秀的路径规划能力,在仓库复杂环境下物料配送的路径规划更合理。MATLAB 2018b仿真环境下的对比实验表明,融合算法能有效减小搜索范围,提升搜索效率,同时也能合理规避静态障碍物和动态障碍物,从而获得更优秀的路径规划效果。

Production practice proves that efficient enterprise production cannot be achieved without the support of production logistics.Material distribution within warehouse is an important part of the production logistics system,and it is often difficult to plan the distribution routes rationally due to the complex obstacle environment within the warehouse.If the distribution routes within the warehouse can be planned rationally,the efficiency of the distribution chain can be increased,which will help to improve production efficiency.This paper takes the improved A*algorithm based warehouse material distribution path planning as the research object.Firstly,the environment of warehouse material distribution path planning is analysed.Secondly,the raster method is used to simulate the warehouse environment and complete the simulation experiments on distribution under the obstacle environment.The search principle of A*algorithm is analysed,and the fusion algorithm is designed by fusing the improved A*algorithm with the Dynamic Window Approach(DWA)algorithm.The improved fusion algorithm will have better path planning capability,which enables more reasonable path planning for material distribution in the complex environment of the warehouse.The comparative experiments by MATLAB 2018b simulation prove that the fusion algorithm can effectively reduce the search range and improve the search efficiency,and also reasonably avoid static obstacles and dynamic obstacles,thus obtaining better path planning results.