Design And Implementation Of AGV Path Optimization Model In Warehousing Logistics System

In recent years,the rapid development of e-commerce has led to the inability of the sorting and distribution efficiency of traditional warehousing and logistics systems to meet the requirements.Therefore,modern intelligent warehousing and logistics came into being.As the cornerstone of the intelligent storage system,the path model optimization problem of AGV intelligent vehicles is becoming an important obstacle to the development of intelligent storage systems.Based on the artificial potential field algorithm model,this paper designs a new improved artificial potential field algorithm model by optimizing and improving it,which improves the success rate and efficiency of the original algorithm model.This paper studies the situation that the artificial potential field algorithm model cannot be successfully executed,and proposes three improvement directions for improving the artificial potential field algorithm model.On this basis,through the elaboration of the gravitational model,the repulsive force model and the resultant force model in the algorithm model,the basic principle of improving the artificial potential field algorithm model is introduced in detail.From the theoretical point of view,the validity,progress and innovation of the improved artificial potential field algorithm model are analyzed.After that,we designed three sets of simulation experiments.In the first set of experiments,a path planning task was performed in multiple environments using an improved artificial potential field algorithm model.The experimental results show that the algorithm model can successfully complete the planning tasks in various scenarios,which verifies the effectiveness of the improved artificial potential field algorithm model.In the second set of experiments,the improved algorithm model proposed in this paper and the traditional artificial potential field algorithm model are used to conduct path planning comparison experiments in multiple environments.The experimental results show that the success rate of path planning using the improved algorithm model proposed in this paper is significantly higher than the traditional algorithm model,which verifies the progress of the improved artificial potential field algorithm model in this paper.In the third set of experiments,path planning comparison experiments were conducted in multiple scenarios using the improved algorithm model of this paper and the mainstream improved algorithm model.The experimental results show that the improved algorithm model in this paper has shorter trajectory length and higher execution efficiency,compared with the mainstream improved algorithm model,which verifies the innovation of the improved artificial potential field algorithm model in this paper.Finally,this paper embeds the improved artificial potential field algorithm model into the routing module in the intelligent AGV management system.Taking a warehouse order processing process as an example,the implementation process and principle of the improved artificial potential field algorithm model in the intelligent AGV management system are introduced,which is proved that the improved artificial potential field algorithm model has practical application value.