Research on docking ring pose estimation method based on point cloud grayscale image

Abstract

The star-arrow docking ring is a ubiquitous structure on space vehicles and is often used as a feature component for pose measurement and capture in non-cooperative space capture missions. When the capture task is performed at a close distance of 0.5 m, due to the high radiation and high light intensity of the space and the coating of the satellite surface with thermal control multilayer materials, the lighting environment is complex, and the grayscale image processing is difficult. The point cloud grayscale image contour feature localization detection method converts the point cloud image into a grayscale image and then estimates the relative pose of the docking ring. Aiming at the problem of fast pose estimation in the case of relative motion, the algorithm adds a fast positioning module of frame image feature area based on the motion model on the original basis, which effectively reduces the feature retrieval area and improves the real-time performance of the algorithm. It is verified by physical simulation experiments. The results show that the method can effectively reduce the influence of stray light and eliminate noise contours. The pose estimation results of the docking ring are accurate and stable, the relative position calculation error is less than 1.5 mm, and the relative pose error is less than 0.45°. The frequency is better than 2 Hz, which meets the needs of real-time capture by space robotic arms.