Far-field target pose vision measurement method based on center standardization

By using a monocular telephoto camera and Levinberg-Marqualt algorithm in the far-field target pose visual measurement system, combined with the central standardization processing, the problems of noise sensitivity and external parameter coupling in the far-field target pose measurement are solved, and high-precision pose measurement and optimization are achieved.

CN119687902AActive Publication Date: 2025-03-25BEIHANG UNIV
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Patent Information

Application Number
CN202411938819.2
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-26
Publication Date
2025-03-25
Estimated Expiration
2044-12-26

AI Technical Summary

Technical Problem

When facing factors such as long-field target pose visual measurement systems, it is difficult to achieve high-precision pose parameter measurement, and conventional methods have strong external parameters coupling, which is easy to fall into local minimum values.

Method used

The far-field target pose visual measurement method based on a monocular telephoto camera is adopted, and the initial value of the pose parameter is obtained through the RPnP method, and nonlinear pre-optimization and subsequent center standardization are carried out in combination with the Levinberg-Marquard algorithm to gradually optimize the pose parameters, and finally high-precision pose measurement is achieved.

Benefits of technology

This method can effectively reduce the sensitivity of pose parameters to image noise, reduce external parameter coupling, avoid falling into local minimum value, and significantly improve the accuracy of far-field target pose visual measurement.

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Abstract

The invention discloses a far-field target pose vision measurement method based on center standardization, and the method comprises the steps: adjusting the pose of a far-field target to be measured, and extracting a far-field target feature point; the method comprises the steps that a far field target pose initial value is solved, a target function is established by minimizing image feature point back projection errors, initial nonlinear optimization is conducted through a Levenberg-Marquardt algorithm to obtain the pose initial value, and parameter pre-optimization is achieved; and after center standardization processing is carried out on the pose parameter Jacobian matrix, nonlinear optimization is carried out by adopting a Levenberg-Marquardt algorithm again, and an optimal solution of the far-field target pose is obtained. The method has the characteristics of reducing the sensitivity of pose parameters to image noise, reducing external parameter coupling, avoiding falling into local minimum and the like, and has important significance in improving far-field target high-precision pose vision measurement in the fields of aerospace and the like.
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