AGV (automated guided vehicle) scheduling method and system adopting inertial navigation based on complex path

Abstract

The invention discloses an AGV (automated guided vehicle) scheduling method and system adopting inertial navigation based on a complex path, and belongs to the field of automatic control. The method comprises the steps as follows: determining an optimal distribution task among a plurality of distribution tasks according to obtained delivery task information with a weighting algorithm; determininga first path, on which the distance between an AGV and a starting node position is the shortest, and a second path, on which the distance between the starting node position and a target node is the shortest, with a graph theory process according to the current node position of the AGV as well as the starting node position, the target node position and a transport network model corresponding to theoptimal distribution task; according to the first path, the second path and a priority-based traffic rule, driving the AGV from the current node to the starting node position, and driving the AGV from the starting node position to the target node position. The method provides an effective, complete and feasible solution for task scheduling and path planning of an AGV system.

Description

technical field [0001] The invention belongs to the field of automatic control, and more specifically relates to an inertial navigation AGV scheduling method and system based on complex paths. Background technique [0002] AGV (English: Automated Guided Vehicle, Chinese abbreviation: Automatic Guided Vehicle) refers to an automatic guided vehicle that can perform specific tasks, and is generally used for material transportation in industrial production. At present, most AGVs adopt fixed path guidance methods, such as electromagnetic guidance and tape guidance. The main feature of these methods is that the technology is relatively mature, but the work of placing information media in the early stage is more troublesome, and the driving path of the car is not flexible enough. Compared with the above-mentioned guidance methods, inertial navigation has the characteristics of advanced technology, high positioning accuracy and strong flexibility, so it is gradually applied to the n...

AI Technical Summary

Problems solved by technology

Because in the time window-based technology, all paths need to be obtained in advance, and the time window needs to be used for one-time planning, that is, tasks are executed in "batch" units, which has poor real-time performance, poor robustness, and inability to plan The probability of finding the best path

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