A scheduling method and system for AGV cluster

By calculating the production rhythm disturbance coefficient and the AGV-task matching model with comprehensive execution suitability, combined with the improved A* algorithm, the scheduling of AGV clusters is optimized, the problems of line stoppage and path conflict at key workstations are solved, and the efficiency of the material handling system is improved.

CN120523201BActive Publication Date: 2025-09-19SHANDONG INSPUR DIGITAL SUPPLY CHAIN TECH CO LTD
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Patent Information

Application Number
CN202511016266.X
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-07-23
Publication Date
2025-09-19
Estimated Expiration
2045-07-23

AI Technical Summary

Technical Problem

Existing AGV cluster scheduling methods fail to effectively identify urgent tasks, resulting in material shortages and production stoppages at key workstations. Path planning is also prone to traffic congestion and conflicts, making it difficult to achieve efficient collaborative operations of AGV clusters.

Method used

By calculating the production rhythm disturbance coefficient and comprehensive execution adaptability, a task allocation model is constructed, and the improved A* algorithm is combined for path planning to optimize AGV-task matching and avoid potential spatiotemporal conflicts.

Benefits of technology

It improves the stability of production rhythm, avoids line stoppages at key workstations, reduces congestion and deadlock between AGVs, and improves the overall efficiency of the material handling system.

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Abstract

The present invention relates to the field of industrial control technology of the Internet of Things. More specifically, it relates to a scheduling method and system for an AGV cluster, the method comprising: calculating a production rhythm disturbance coefficient; performing weighted calculation on the production rhythm disturbance coefficient and the comprehensive execution suitability of the AGV to obtain an allocation utility value; constructing a task allocation model with the goal of maximizing the sum of the allocation utility values ​​of all possible allocations, and solving the model to obtain the optimal AGV-task allocation pair; for the determined AGV-task allocation pairs, planning driving paths for the AGVs in descending order of the production rhythm disturbance coefficients of their tasks; wherein, an improved A* algorithm is adopted, and a space-time conflict probability cost is superimposed when calculating the passage cost of the path segment; and the driving path is sent to the corresponding AGV for execution. The present invention improves the success rate of path planning and the passage efficiency of AGVs, making the entire logistics system run more smoothly and efficiently.
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