Chinese Space Science and Technology ›› 2025, Vol. 45 ›› Issue (5): 132-142.doi: 10.16708/j.cnki.1000-758X.2025.0081

Previous Articles     Next Articles

Real time pose measurement of space non-cooperative targets at ultra-close range based on ICP algorithm

ZHAO Hanxue,HU Jiaqian,SHAO Changbao,JIANG Haitian,LI Shuang*   

  1. College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • Received:2024-06-03 Revision received:2024-09-07 Accepted:2024-09-11 Online:2025-09-17 Published:2025-10-01

Abstract: To address the limitations of traditional methods in meeting the real-time and high-precision requirements for ultra-close-range pose measurement tasks, this paper proposes a ultra-close-range real-time pose measurement method of space non-cooperative target based on the Iterative Closest Point (ICP) algorithm. The proposed approach integrates high-precision pose estimation for keyframes with real-time pose tracking for non-keyframes. Initially, statistical filtering was applied to keyframes for point cloud denoising to enhance computational efficiency. The point cloud was then sparsified using a downsampling method based on the centroid of neighboring points within the voxel grid. Subsequently, a combination of coarse registration and ICP was employed to determine the pose of keyframes relative to the target model, thus achieving pose estimation for keyframes. For non-keyframes, uniform downsampling coupled with ICP was used to capture real-time pose changes between consecutive non-keyframes, facilitating pose tracking. Finally, the real-time pose tracking of non-keyframes was fused with pose estimation of keyframes to eliminate the cumulative errors and obtain high-precision, real-time pose measurements. Simulation results demonstrate that the proposed algorithm can achieve real-time pose measurement for close-range non-cooperative targets and its computational frequency can reach 24Hz, with an attitude error of no more than 1° and a position error within 2centimeters. These findings suggest that the proposed algorithm, designed with novel architectures based on the traditional ICP method, achieves high-precision pose estimation for keyframes and real-time position tracking for non-keyframes. The accumulative error of real-time pose tracking is suppressed by fusing high-precision pose estimation. This approach ensures real-time performance while meeting the high-precision requirements of ultra-close-range measurement tasks involving non-cooperative targets.

Key words: statistical filtering, ICP, pose measurement, noncooperative targets in space; , ultra-close-range real-time measurement, voxel downsampling