A visual data preprocessing method for double-ball nested rolling robot

By using a method of simultaneous acquisition of visual and IMU attitude data and multi-level processing, the problems of rotation compensation and blur removal of visual data in a nested double-ball rolling robot were solved, thereby improving image stability and navigation accuracy.

CN122820850APending Publication Date: 2026-09-25HUALU YIYUN TECH CO LTD +1
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Patent Information

Application Number
CN202611282230.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-08-24
Publication Date
2026-09-25

AI Technical Summary

Technical Problem

Existing technologies fail to effectively combine the spherical rolling characteristics of nested double-ball rolling robots, resulting in visual data exhibiting periodic rotation, motion blur, and field-of-view fluctuations, which affect the accuracy and stability of navigation and target detection.

Method used

The system employs simultaneous visual and IMU attitude acquisition, fisheye distortion correction, spatiotemporal alignment, and frame grouping. It combines Madgwick attitude calculation and motion blur kernel estimation, performs rolling geometry compensation and adaptive Wiener filtering, performs regional exposure equalization and region of interest enhancement, and finally performs inter-frame stabilization through sparse optical flow registration and temporal smoothing.

Benefits of technology

It achieves precise compensation and blur removal for spherical rolling motion, improves image stability and clarity of key navigation information, and meets the autonomous navigation needs of robots.

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Abstract

The present application relates to the technical field of robot vision data processing, and discloses a kind of for double ball nesting type rolling robot visual data preprocessing method, comprising: collecting robot vision image data and attitude sensing data and pre-processing;Based on attitude data, identify the rolling motion state of sphere, output motion blur kernel parameter and attitude angle sequence;Rolling geometry compensation and adaptive deblurring processing are executed, and the image frame after correction deblurring is output;After correction image is carried out regional exposure equalization and direction region of interest enhancement, and output enhanced image sequence;After interframe registration and time sequence smoothing processing, output standardization vision data, and registration residual error is fed back to optimize motion blur estimation.The present application is aimed at the spherical surface rolling characteristics of double ball nesting type rolling robot, and realizes hierarchical preprocessing by fusing attitude and vision data, effectively solves the problems of picture rotation, motion blur and field fluctuation caused by rolling, and significantly improves the quality and stability of vision data.
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