Intelligent scheduling system and method for multiple automatic guided vehicles in automated wharf

Abstract

The invention relates to an intelligent dispatching system and method for a multi-AGV (Automatic Guided Vehicle) of an automatic container terminal. The two-stage distribution control dispatching mode of an operation plan and dispatching decoupling separation is realized through a container terminal management information system and an AGV group intelligent dispatching system. A knowledge learning method is used; an AGV dispatching knowledge management module is built; an AGV task case base, a path case base and a knowledge base are continuously enriched and optimized; and the AGV self learning, self organization and self decision capability are improved. Through the rolling prediction on traffic flow in a road network space of the automatic container terminal and the calling of the knowledge base, the AGV task case base and the path case base, the collaborative optimization is performed on the task dispatching and the path planning of AGVs. The invention provides an AGV path planning strategy including the optional path and free path mode; the path plan in the conventional task can be ensured; and the fast response measures can also be provided for emergency tasks.

Description

technical field [0001] The invention relates to an intelligent scheduling system and method for multiple automatic guided vehicles in an automated wharf. Background technique [0002] Automated terminal operation scheduling mainly includes three links: quayside crane operation, horizontal transportation operation and yard operation. The automatic guided vehicle (Automatic Guided Vehicle, referred to as AGV) horizontal transportation is an important link connecting the quay crane operation and the field bridge operation, and is the mainstream method of horizontal transportation in the current automated terminal. Different from the bottleneck of the traditional quay crane and field bridge operation system, on the one hand, in the modern automated terminal, the container operation volume and horizontal transportation distance have greatly increased, and the loading and unloading capacity of the quay bridge and field bridge has been greatly improved; on the other hand, Due to t...

AI Technical Summary

Problems solved by technology

In short, this scheduling mode is static, and the decision-making efficiency is low, which hinders the improvement of job efficiency

[0006] (2) Static path planning is difficult to avoid spatio-temporal interference, which is likely to cause traffic congestion and deadlock

[0007] (3) Lack of a priority allocation mechanism for emergency tasks, and insufficient emergency response capabilities for failures and emergencies

For faults and emergencies, they are mainly dealt with manually after the event, and there is still a lack of emergency task priority mechanism. Functionally, AGV autonomous collaborative avoidance and emergency task quick execution measures (such as free path driving) have not yet been realized.

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