AGV System Design And Key Technology Research

AGV car is an automatic guided vehicle,which is an automatic workshop and one of the important components of intelligent unmanned storage equipment.At present,with the development of flexible manufacturing and national economy,more and more cars are put into the environment of large workshop and warehouse.At this stage,the research of AGV trolleys is mainly to transport workpieces and raw materials along the prescribed route in the workshop environment.In the storage environment,the AGV car which can save energy,complete the optimal path fast planning and improve the working efficiency to the maximum is the key and difficult point of each intelligent equipment research institute.For the method of AGV trolley and its path planning in a smart storage environment,the main work includes two parts: designing and assembling a complete AGV car,and using Bat Algorithms to optimize the path planning task.The specific work is as follows:First of all,the research status of AGV car at home and abroad,as well as the existing path planning methods are analyzed,and the main content and structure of this paper are introduced.Secondly,the intelligent storage model is established as the experimental platform for the domestic large-scale storage environment,which makes the research more in Generality.According to the multi-layer experimental platform,the Grid Method is used to complete the corresponding map modeling.Thirdly,a four-wheel AGV and an eight wheel AGV that can travel in four directions without turning the body was designed.Then,according to the map modeling model,by using the Time Window Algorithm to solve the problem of car conflict,by combining Bat Algorithms with Artificial Potential Field Method to complete the path planning of multi AGV vehicle in intelligent storage environment.Finally,MATLAB Simulation is used to verify The Proposed Algorithm.At the same time,the final optimization results are proved by using the storage platform andthe car.The experimental results show that the path planning method and the car have better control effect and the ability of seeking the optimal path to improve work efficiency.