Multi-AGV equipment cooperative scheduling method and system based on artificial intelligence

By establishing a digital twin simulation model and collaborative scheduling algorithm, the problem of inefficiency of traditional AGV scheduling methods in complex environments is solved, and efficient collaborative work and path optimization of multiple AGV devices are realized.

CN120406458APending Publication Date: 2025-08-01SHENZHEN SANYOU INTELLIGENT AUTOMATION EQUIP CO LTD
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Patent Information

Application Number
CN202510548811.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-04-28
Publication Date
2025-08-01

AI Technical Summary

Technical Problem

Traditional AGV scheduling methods are difficult to dynamically adapt to changes in task requirements in complex environments, resulting in unreasonable task allocation and unbalanced load, and difficult to adjust path planning in real time, resulting in path conflicts and inefficiency, lack of multi-AGV collaboration mechanisms, and serious waste of resources.

Method used

By obtaining the motion parameters and task path data of AGV devices in real time, establishing a digital twin simulation model, performing path simulation and collision analysis, calculating the priority of the device, and performing coordinated scheduling to avoid collisions and optimize paths.

Benefits of technology

It realizes efficient collaborative work of AGV equipment in complex environments, improves the rationality of task allocation and real-time path planning, reduces resource waste, and improves system efficiency.

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Abstract

The invention relates to an intelligent scheduling technology, and discloses a multi-AGV device cooperative scheduling method and system based on artificial intelligence, and the method comprises the steps: obtaining the motion parameters of each AGV device in real time, obtaining the task path data of each AGV device, building a digital twinborn simulation model according to the motion parameters and the task path data, and carrying out the calculation of the digital twinborn simulation model. Simulating a future path of each AGV device based on the digital twin simulation model to obtain simulated path data based on a time sequence, identifying time data of each AGV device arriving at each preset key node according to the simulated path data, obtaining an arrival time set of each key node, and obtaining an arrival time set of each key node; and carrying out AGV equipment collision analysis according to the arrival time set to obtain a collision analysis result, and carrying out cooperative scheduling on the AGV equipment according to the collision analysis result. According to the invention, the multi-AGV equipment scheduling efficiency can be improved.
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