An AGV visual positioning system based on edge computing

The AGV visual positioning system using edge computing utilizes segment modeling and event triggering techniques, combined with inertial and wheel speed information to calculate pose, and performs consistency verification at edge nodes. This solves the problems of high computational resource consumption and difficulty in verifying positioning results in existing AGV visual positioning methods, achieving efficient and stable positioning results.

CN122108140APending Publication Date: 2026-05-29SONGMENG (BEIJING) ROBOT CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
SONGMENG (BEIJING) ROBOT CO LTD
Filing Date
2026-03-04
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

Existing AGV visual positioning methods consume high computational resources and consume a lot of power, are prone to introducing redundant information, and make it difficult to verify and correct positioning results in a timely manner. Furthermore, they do not fully utilize the computing power of edge nodes.

Method used

An edge computing-based AGV vision positioning system is adopted. A segment positioning list is generated through segment modeling, visual change information is obtained by using event triggering, and pose calculation is performed by combining inertial information and wheel speed information. Consistency verification and pose correction are performed at edge nodes.

Benefits of technology

It reduces computing resource consumption and power consumption, improves the stability and reliability of positioning, enables timely verification and correction of positioning results, reduces redundant observation data, and enhances the real-time performance and accuracy of positioning.

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Abstract

The application discloses an AGV visual positioning system based on edge calculation and relates to the technical field of visual positioning.The AGV acquires visual change information through an event triggering mode in a driving process based on a section constraint set, collects corresponding image information, inertial information and wheel speed information when a triggering condition in the section constraint set is met, forms observation data, a pose solution module, the AGV performs pose solution by using the observation data and geometric coding landmark information in the section constraint set, obtains a current pose, synchronously generates a positioning availability level and corresponding cooperative request data, an edge checking module, after the edge node receives the cooperative request data, the current pose is checked for consistency according to the section constraint set and a pose correction amount is calculated; the application collects image, inertial and wheel speed data only when the triggering condition is met, avoids the calculation burden caused by continuous image collection and high-frequency feature extraction, and effectively reduces the generation of redundant observation data.
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