Using consecutive point clouds for pose and motion estimation of tumbling non-cooperative target

作     者：Li, Yipeng Wang, Yunpeng Xie, Yongchun 

作者机构：Beijing Inst Control Engn Beijing 100190 Peoples R China Sci & Technol Space Intelligent Control Lab Beijing 100094 Peoples R China Tianjin Key Lab Micrograv & Hypograv Environm Sim Tianjin 300301 Peoples R China 

出 版 物：《ADVANCES IN SPACE RESEARCH》 (空间研究进展)

年 卷 期：2019年第63卷第5期

页      面：1576-1587页

核心收录：

学科分类：08[工学] 0708[理学-地球物理学] 0706[理学-大气科学] 0704[理学-天文学] 0825[工学-航空宇航科学与技术] 

基　　金：National Key Basic Research and Development Program [2013CB733100] National Natural Science Foundation of China [61333008, 61603037] 

主　　题：Non-cooperative target Consecutive point clouds Consistent pose estimation Pose graph optimization EKF 

摘      要：This paper proposes a consecutive point clouds-based estimation scheme to resolve the state estimation problem for tumbling noncooperative space target during the rendezvous phase without a prior knowledge about its structure. First, a consistent pose estimation algorithm is realized by maintaining a global structure of the target that is reconstructed upon the pose graph optimization. Then an extend Kalman filter on Lie group is adopted to estimate the motion and inertia parameters of the target using the pose measurements of the point clouds. Finally, a semi-physical experimental study is carried out to evaluate the performance of the proposed estimation scheme. The result shows that the structure, motion and the inertia parameters can be estimated, and the total computation time is approximately linear with the number of point clouds. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.