Yin Fang, Chou Wusheng, Wu Yun, Yang Guang, Xu Song
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, China.
State Key Laboratory of Virtual Reality Technology and Systems, Beihang University, Beijing 100191, China.
Sensors (Basel). 2018 Mar 28;18(4):1009. doi: 10.3390/s18041009.
This paper proposes an autonomous algorithm to determine the relative pose between the chaser spacecraft and the uncooperative space target, which is essential in advanced space applications, e.g., on-orbit serving missions. The proposed method, named Congruent Tetrahedron Align (CTA) algorithm, uses the very sparse unorganized 3D point cloud acquired by a LIDAR sensor, and does not require any prior pose information. The core of the method is to determine the relative pose by looking for the congruent tetrahedron in scanning point cloud and model point cloud on the basis of its known model. The two-level index hash table is built for speeding up the search speed. In addition, the Iterative Closest Point (ICP) algorithm is used for pose tracking after CTA. In order to evaluate the method in arbitrary initial attitude, a simulated system is presented. Specifically, the performance of the proposed method to provide the initial pose needed for the tracking algorithm is demonstrated, as well as their robustness against noise. Finally, a field experiment is conducted and the results demonstrated the effectiveness of the proposed method.
本文提出了一种自主算法，用于确定追踪航天器与非合作空间目标之间的相对姿态，这在诸如在轨服务任务等先进空间应用中至关重要。所提出的方法名为全等四面体对齐（CTA）算法，它使用由激光雷达传感器获取的非常稀疏的无组织三维点云，并且不需要任何先验姿态信息。该方法的核心是基于已知模型，通过在扫描点云和模型点云中寻找全等四面体来确定相对姿态。构建了两级索引哈希表以加快搜索速度。此外，在CTA之后使用迭代最近点（ICP）算法进行姿态跟踪。为了在任意初始姿态下评估该方法，提出了一个模拟系统。具体而言，展示了所提出方法提供跟踪算法所需初始姿态的性能，以及它们对噪声的鲁棒性。最后，进行了现场实验，结果证明了所提出方法的有效性。
