| With the development of logistics in the direction of intelligence and wisdom,the automated operation mode gradually replaces the human operation mode.Automated Guided Vehicle(AGV),an important intelligent equipment in modern logistics and warehousing operations,is mainly responsible for the handling and picking of goods,which greatly improves the efficiency of warehousing operations and reduces labor costs.Multi-storage AGVs can complete multiple picking tasks in a single trip.The walking sequence problem of multi-storage AGVs in the actual picking operation needs to be planned with the actual operation scenario,and the solution to the conflict problem of multi-AGV systems needs to be in line with the actual operation logic in order to achieve a global picking path planning without conflict.This paper takes multi-storage AGV as the research object,analyzes the operation environment and operation characteristics of multi-storage AGV by comparing three common environment map modeling methods,and selects the raster map method to complete the environment map modeling.The picking path problem of a multi-storage AGV is analyzed and transformed into a two-stage problem: the first stage is the calculation of the shortest path among task nodes,and the second stage is the planning of the walking sequence between the picking nodes.By comparing several common path planning algorithms,this paper takes A* algorithm as the basis of path planning algorithm,and combines the actual operation scenario to weight Manhattan distance and introduces steering correction coefficient to improve the algorithm search efficiency and reduce steering time.This walking order planning problem while picking task is transformed into a 0-1 planning problem,a mathematical model is built,and a depth-first traversal algorithm is selected to solve the walking order planning problem.With the planning of global conflict-free paths for multi-storage AGVs as the research objective,this paper first introduces the concept of time window,establishes a time window model,and defines calculation formulas for the scenarios requiring time window calculation in the paper,and then this paper analyzes the conflict problem in actual operation scenarios,divides the conflict problem into: phase conflict,intersection conflict and catch-up conflict,and gives definitions.Secondly,for different conflict scenarios,three conflict resolution strategies are proposed to solve the conflict problem,and the discriminative methods of different conflict types based on time windows are given.Finally,a global path planning model is built to transform the path shortest problem into the total picking time shortest problem,and a two-stage path planning algorithm with fused time windows is proposed to sort out the algorithm steps and flowcharts as a global path planning algorithm for multi-storage AGVs.This paper uses the automated stereo warehouse of Company A as the experimental background to set the experimental parameters,and conducts simulation experiments using MATLAB.The experiment generates random picking tasks,and then solves the pairwise short paths between each task node using the improved A* algorithm.After planning the walking paths and comparing the results using three algorithms,the depthfirst traversal algorithm is the most effective way to find the optimal picking order.We use the two-stage path algorithm with fused time windows to do the experiments and the experimental results show that the AGV steers 1.69 times per task sub-path on average,and the steering correction factor plays an important role.The types and numbers of conflicts in the system are counted,and the operational effects of using the conflict resolution strategy are analyzed.The conflicts in the system are all resolved,and finally the performance of the algorithm in different environments is analyzed using large-scale experiments,which proves that the algorithm has some practical value.There are 35 figures,17tables and 41 references in this paper. |
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