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Design Of Multi AGV Cooperative Scheduling System Based On Agent

Posted on:2021-12-07Degree:MasterType:Thesis
Country:ChinaCandidate:J X MiaoFull Text:PDF
GTID:2492306107968639Subject:Control Engineering
Abstract/Summary:PDF Full Text Request
With the progress of industrialization,automatic guided vehicle has become an important material handling tool in modern logistics equipment.The collaborative scheduling ability of AGV system is directly related to the efficiency of the whole logistics(production)system,and how to design an efficient and stable multi-AGV collaborative scheduling system is an urgent problem to be solved in the industry.Firstly,there are two control methods in the field of multi-AGV system:centralized control and distributed control.By analyzing and contrasting the advantages and disadvantages of these two controlling structures,determines the design of a distributed multi-AGV collaborative scheduling system based on intelligence.At the same time,the organizational structure of single AGV system is designed.Secondly,with the analysis and comparison of the mainstream wireless communication technology selected Zig Bee,which is more suitable for application in the distributed system architecture,as the main communication,and clarified the networking mode of Zig Bee system.And completed the communication system software development work.Thirdly,Then,in the question of AGV’s path planning,an optimized A-algorithm based on the priority queue of the binary heap is proposed.In the problem of AGV’s barrier avoidance,a barrier avoidance strategy that optimizes the artificial potential field method of potential field function is adopted.A grouping contract network algorithm is proposed in the problem of AGV’s task allocation.Finally,a multi-AGV communication environment is set up in JADE’s platform to test the key issues of communication and collaboration to ensure stable communication and collaboration between multi-intelligence bodies.
Keywords/Search Tags:Automatic Guide Trolley, Smart Body, Improved A* algorithm, Artificial Field Method
PDF Full Text Request
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