Accurate Pose Measurement Based on Stereo Vision for Satellite Assembly Systems

Accurate measurement of panel and frame poses is essential for achieving automated and high-precision satellite assembly. Feature-holes distributed across the satellite’s mating surfaces typically serve as assembly and measurement reference points. However, the various types of feature-holes, coupled with issues such as high reflectivity, edge occlusion, and surface defects, lead to the limitation of pose measurement accuracy and robustness based on feature-holes. To address this challenge, a high-precision component pose measurement method based on stereo vision is proposed. First, a contour splitting and merging method based on geometric structural consistency (GSC) is developed to ensure low noise and high integrity of the contour. Next, to enhance feature-hole recognition accuracy and efficiency, a partitioned weighted sampling and iterative consistency (PWS-IC) strategy is introduced. Finally, to further improve measurement robustness, a component pose estimation method is proposed that effectively reduces the impact of outliers on pose estimation accuracy. Experimental results demonstrate that the measurement accuracy of feature-holes reaches 0.03 mm, whilst the position and attitude estimation accuracy of satellite components attain 0.05 mm and 1.1×10-5 degrees, respectively. Compared with existing methods, the proposed approach achieves substantial improvements in both accuracy and robustness. When applied to satellite assembly, the achieved mating accuracy reaches 0.15 mm, satisfying the technical requirement of 0.2 mm.