Laser & Optoelectronics Progress, Volume. 56, Issue 14, 141503(2019)

Point Cloud Registration Based Satellite Motion Parameter Identification Method

Rongrong Lu1,2,3,4, Haibo Sun1,4,5, Shuangfei Fu1,2,4、*, Feng Zhu1,2,4、**, and Yingming Hao1,2,4
Author Affiliations
  • 1 Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 2 Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 3 University of Chinese Academy of Sciences, Beijing 100049, China
  • 4 Key Laboratory of Opto-Electronic Information Process, Chinese Academy of Sciences, Shenyang, Liaoning 110016, China
  • 5 Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning 110819, China
  • show less

    A non-contact satellite motion parameter identification method is proposed for the derotation of satellites that roll in space while simultaneously spinning and precessing. The algorithm involves three main steps. First, the point-cloud registration is used to obtain the pose transformation between two adjacent point clouds, from which the trajectories of the points in the satellite’s point cloud are obtained. Second, because the points on the spin axis only rotate around the moving axis, the principal component analysis and circle-fitting method are used to find a point on the spin axis and thereby determine the direction and position of the precession axis. Finally, the rolling satellite’s parameters are found by solving a set of nonlinear equations, established based on the relationships between the overall pose transformation and the two motions. The simulation results show that the proposed method can accurately identify the motion parameters of a rolling satellite for certain noise levels.

    Tools

    Get Citation

    Copy Citation Text

    Rongrong Lu, Haibo Sun, Shuangfei Fu, Feng Zhu, Yingming Hao. Point Cloud Registration Based Satellite Motion Parameter Identification Method[J]. Laser & Optoelectronics Progress, 2019, 56(14): 141503

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category: Machine Vision

    Received: Dec. 4, 2018

    Accepted: Feb. 22, 2019

    Published Online: Jul. 12, 2019

    The Author Email: Fu Shuangfei (yunfei@sia.cn), Zhu Feng (fzhu@sia.cn)

    DOI:10.3788/LOP56.141503

    Topics