Measurement mark tracking method and device based on AI vision

By using a tightly coupled fusion algorithm of AI vision and IMU, the reliability and accuracy issues of visual tracking under complex working conditions are solved, achieving high-precision marker tracking, which is suitable for scenarios such as drone inspection, industrial assembly and autonomous driving.

CN121783093APending Publication Date: 2026-04-03NANJING RUNZHONG TESTING TECH CO LTD
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Patent Information

Application Number
CN202610086473.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-22
Publication Date
2026-04-03

AI Technical Summary

Technical Problem

In complex working conditions, traditional vision-based marker tracking methods are limited by the reliability and accuracy of a single sensor, making it difficult to achieve stable and accurate target tracking, especially under conditions such as changes in ambient lighting, dynamic motion blur, and marker point blur.

Method used

By employing a tightly coupled fusion algorithm combining an AI visual perception module and an IMU inertial measurement module, and integrating a visual information acquisition device and an IMU sensor, the motion trajectory and position data of the target device are calculated through data preprocessing and the tightly coupled fusion algorithm, thereby achieving high-precision marker tracking.

Benefits of technology

It achieves real-time, stable, and high-precision measurement in complex environments, and is suitable for scenarios such as drone inspection, industrial assembly, and autonomous driving, overcoming the problems of environmental interference and IMU drift.

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Abstract

The invention belongs to the technical field of AI vision measurement, and particularly relates to a measurement mark tracking method and device based on AI vision, and the device comprises an AI vision perception module, an IMU inertial measurement module, a data fusion calculation module and an execution control module, the visual information acquisition device is deployed on a measurement object; through fusion of AI vision and IMU, interference of complex working conditions such as environment illumination change, dynamic motion blurring, camera motion and mark point blurring on measurement operation is overcome, the problems that single vision tracking is easily interfered by the environment and single IMU tracking has accumulative drifting are solved, real-time, stable and high-precision measurement in the complex environment is achieved, and the measurement precision is improved. The method can effectively adapt to various measurement scenes such as unmanned aerial vehicle inspection, industrial assembly, automatic driving calibration and the like.
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