Research On Centralized Control And Dispatching System Of Multi-AGV Intelligent Parking Garage

Witj the economic development and social progress,the car ownership has been sharply improved,the number of private cars continues to grow rapidly and the urban traffic environment has gradually deteriorated,and the serious shortage of urban parking spaces has become one of the main factors restricting urban development.In order to alleviate the pressure of urban management due to "difficult parking",large-scale intelligent parking lots came into being.This paper focuses on the path planning and scheduling of multiple AGVs in smart parking lots.Starting from the actual application scenarios of smart parking lots,this paper analyzes the causes of multi-AGV deadlocks when performing tasks.Through rational optimization of task allocation,the design is based on task emergency The dynamic priority strategy of the degree and relative waiting time index improves the overall operation efficiency of AGVS,ensures that the dispatch system accesses vehicles quickly and efficiently.This dispatch system helps the reasonable allocation of parking space resources and reduces the traffi congestion index in the city.The main research contents of this article are as follows:Firstly,Analyze the existing parking lot's intelligence degree,layout status and environmental characteristics,and design the environmental layout of the smart parking lot according to the characteristics of multi-AGV full-automatic access vehicles.Based on the topology optimization method,the actual environment is convertecd into an electronic map of a smart parking lot,and the related environmental layout features in the electronic map are parameterized,which can be used for rapid modeling of more electronic maps in different field environments.The A*algorithm is used to plan the global optimal motion path of the AGV in the static road network of the parking lot electronic map,which effectively improves theefficiency of accessing the car,With the dynamic update of the electronic map,the position and status of the AGV can be observed in real time,and the task execution status of the AGV can be understood in time.Secondly,according to the layout of intelligent parking lot,a multi-AGV task scheduling model was established.Combined with the characteristics of the environmental structure of the intelligent parking lot,it is determined that the shortest path,the smallest travel time and the highest transportation efficiency are taken as the compound scheduling target.According to the task urgency and the relative waiting time,the dynamic priority task queuing method is adopted to realize the multi-AGV global optimal real-time scheduling of executing tasks.A time window prediction algorithm is used to detect conflicts in all planned paths of the AGV.The proposed conflict resolution strategy can deal with the problem of overlapping overlapping paths at the same time and update the time window data in real time.Predict the execution time of each AGV task,draw the time window distribution map of each AGV task,and use the waiting method and path re-planning method to solve the problem of multiple AGV conflicts for the time window with overlapping parts,so that the AGVs of all task executions get an overall Optimal path.Through scheduling simulation examples,the feasibility of scheduling method is verified.Thirdly,Development of intelligent parking lot dispatch management system.The system is composed of user usage layer,logic layer,support layer and basic data layer.The user layer includes sub-function modules such as electronic map modeling,task scheduling,and user management.Users can operate the functions of related modules to achieve corresponding needs.The logic layer is used to formulate the multi-AGV composite scheduling target and execute the queuing algorithm for multi-task delivery,respond to the requests from the user layer in time,and read the real-time environment and operating data through the data support layer.The data layer provides all the basic data required by the scheduling system,and uses the SQL Server database to dynamically manage the data and update it in time.Finally,the multi-functional AGV experiment platform independently developed by the laboratory and the three DrRobot 190 scheduling experiment platform verify the effectiveness and feasibility of the scheduling system using A*algorithm to plan the optimal path and the function of each module.Three DrRobot 190 mobile robots verify the correctness of the scheduling model and the rationality of multiple AGVs encountering conflict avoidance when performing tasks.The experimental results show that the intelligent parking lot AGVS scheduling management system developed in this paper can effectively improve the collision and deadlock of AGV in the process of multi-AGV task assignment and task execution.