摘要
为了实现空间翻滚卫星(同时作自旋和进动的卫星)的消旋,提出了一种非接触式的卫星运动参数辨识方法。算法主要包含3个步骤:通过点云配准技术,获取相邻两幅点云之间的位姿变换关系,从而可以依据这些位姿变换得到卫星点云中每个点的运动轨迹;基于自旋轴上的点只绕进动轴旋转的特点,借助主成分分析与圆拟合的方式,搜索自旋轴上的点并确定进动轴的方向和位置;根据整体位姿变换与两种运动间的关系,建立非线性方程组求解出翻滚卫星的运动参数。仿真实验结果表明,在一定的噪声程度下,所提方法可以准确地辨识出空间翻滚卫星的运动参数。
A non-contact satellite motion param eter 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 transform ation 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 param eters are found by solving a set of nonlinear equations, established based on the relationships between the overall pose transform ation and the two motions. The simulation results show that the proposed method can accurately identify the motion param eters of a rolling satellite for certain noise levels.
作者
鲁荣荣
孙海波
付双飞
朱枫
郝颖明
LuRongrong;Sun Haibo;FuShuangfei;Zhu Feng;HaoYingming(Shenyang Institute of Automation ,Chinese Academy of Sciences,Shenyang, Liaoning 110016,China;Institutes for Robotics and Intelligent Manufacturing,Chiyiese Academy of Sciences,Shenyang,Liaoning W0016,China;University of Chinese Academy of Sciences,Beijing 100049,China;Key Laboratory of Opto-Electrcmic Inform ation Process, Chinese Academy of Sciences,Shenyang,Liaoning 110016,China;Faculty of Robot Science and Engineering,Northeastern University,Shenyaiig,Liaoning 110819,China)
出处
《激光与光电子学进展》
CSCD
北大核心
2019年第14期203-212,共10页
Laser & Optoelectronics Progress
基金
创新基金(CXJJ-17S032)
关键词
机器视觉
点云配准
卫星消旋
参数辨识
运动估计
machine vision
point cloud registration
derotation of satellites
param eter identification
motion estimation