Aiming at the impact of multiple factors on the accuracy of monocular visual pose measurement system, grey correlation method is used to analyze the pose measurement errors of 11 independent variable parameters, including radial distortion error, tangential distortion error, image point error, normalized focal length error and center point error. The main factors affecting the pose accuracy are obtained, which proves the effectiveness of the grey correlation method for visual system error analysis. The calculation results show that the comprehensive correlation degree between absolute error sequence and zero sequence caused by five types of parameters of radial distortion, tangential distortion, image point coordinate error, normalized focal length error and center point error is less than 0.56, which is significantly lower than other parameters, indicating that its influence on measurement accuracy is significantly higher than other parameters.
KEYWORDS: Monte Carlo methods, Imaging systems, Distortion, Cameras, Visual process modeling, Optical engineering, Mathematical modeling, Systems modeling, Tolerancing, Statistical analysis
Due to the influence of many factors in monocular vision pose measurement, the reliability of pose measurement results needs to be evaluated by uncertainty. The difficulties of the traditional guide to the expression of uncertainty in measurement (GUM) method in actual pose evaluation are analyzed, and the adaptive Monte Carlo method (AMCM) is used to evaluate the uncertainty of pose results. According to the mathematical model of pose measurement, the factors affecting pose results are analyzed in detail. The uncertainty evaluation model is established by the error traceability method and the distribution of uncertainty components is analyzed reasonably. Both the Monte Carlo method (MCM) and AMCM are used to evaluate the uncertainty of pose results. The feasibility and effectiveness of the AMCM evaluation method are verified. The experimental results show that MCM and AMCM, as the supplement of the GUM method, can well solve the problem of pose evaluation in the actual measurement system. However, AMCM is more convenient and efficient than MCM to solve the problem of too large or too small sampling times.
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