An AGV forklift collaborative scheduling method and system for smart warehouse management

Through the AGV forklift collaborative scheduling method for smart warehousing management, and using improved path planning and collaborative scheduling algorithms, the problem of insufficient stability and reliability of AGV forklift collaborative scheduling in the existing technology is solved, and efficient AGV forklift collaborative scheduling and operation efficiency is improved.

CN118863472BActive Publication Date: 2025-03-25ZHEJIANG ZHONGYANG STORAGE TECH CO LTD
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Patent Information

Application Number
CN202411325110.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2024-09-23
Publication Date
2025-03-25
Estimated Expiration
2044-09-23

AI Technical Summary

Technical Problem

In the prior art, the main node election method of AGV forklift coordinated scheduling is overly dependent on decision-making, resulting in insufficient stability and reliability, and it is difficult to achieve efficient operation coordination.

Method used

A collaborative scheduling method for AGV forklifts for smart warehousing management is proposed. By obtaining the two-dimensional map data of the target warehousing area, a dynamic task chain is constructed, and a path planning is used to predict conflicting road sections is predicted. A collaborative scheduling model is constructed based on the cuckoo search algorithm, and the best conflict coordination strategy is selected.

Benefits of technology

It improves the stability and reliability of the AGV forklift system, realizes efficient coordinated scheduling of multiple AGV forklifts, and improves operating efficiency and safety.

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Abstract

The present invention discloses a collaborative scheduling method and system for AGV forklifts for intelligent warehouse management, including: obtaining two-dimensional map data of the target warehouse area, adding virtual nodes in the topological map model according to the transportation tasks of the target warehouse area, and constructing a dynamic task chain; improving the A* algorithm by using the motion characteristics of the AGV forklift, and obtaining the global optimal path through the improved A* algorithm based on the dynamic task chain; using the fusion A* algorithm and the dynamic window method to optimize the local path, predicting the conflicting sections and conflict types that will occur in the AGV forklift group; constructing a collaborative scheduling model based on the cuckoo search algorithm, initializing the conflict coordination strategy, selecting the best conflict coordination strategy, and realizing the collaborative scheduling of multiple AGV forklifts. The present invention obtains the best planned path for the AGV forklift to improve stability and reliability, and improves the operating efficiency through intelligent coordination strategy selection.
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