A Calibration and Error Evaluation Method of a Combined Tracking-Based Vision Measurement System for Meter-Scale Components

Abstract

Combining a global tracking system with a local measurement system constitutes an efficient approach for meter-scale component measurement. The transformation matrix between the local system and the transfer target is critical in the global integration of local data. This article proposes an enhanced calibration methodology for the combined track-based vision measurement system. A calibration equation based on the system data transformation and scale factor is established. Then theoretical and optimal solutions for the transformation matrix were derived. Subsequently, a statistical analysis is conducted to assess the error distribution and the impact of error sources on global measurement accuracy. Notably, the influence of the scale factor on the global error presents a linear pattern. Both simulation and experimental validations demonstrate that our calibration approach achieves high precision in determining the transformation matrix and global positioning. Specifically, the repeatability of positioning and the accuracy of data stitching between multiple viewpoints are both lower than 0.1 mm. The flatness of the point cloud stitched from two perspectives using a planar calibration board is 0.025 mm. Consequently, the proposed calibration strategy enables the accurate 3D reconstruction of meter-scale components while preserving local accuracy.