Point Cloud Based Relative Pose Estimation of a Satellite in Close Range.
Determination of the relative pose of satellites is essential in space rendezvous operations and on-orbit servicing missions. The key problems are the adoption of suitable sensor on board of a chaser and efficient techniques for pose estimation. This paper aims to estimate the pose of a target satellite in close range on the basis of its known model by using point cloud data generated by a flash LIDAR sensor. A novel model based pose estimation method is proposed; it includes a fast and reliable pose initial acquisition method based on global optimal searching by processing the dense point cloud data directly, and a pose tracking method based on Iterative Closest Point algorithm. Also, a simulation system is presented in this paper in order to evaluate the performance of the sensor and generate simulated sensor point cloud data. It also provides truth pose of the test target so that the pose estimation error can be quantified. To investigate the effectiveness of the proposed approach and achievable pose accuracy, numerical simulation experiments are performed; results demonstrate algorithm capability of operating with point cloud directly and large pose variations. Also, a field testing experiment is conducted and results show that the proposed method is effective.
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China. liulujiang@njust.edu.cn.
Lujiang
L
Liu
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China. zhaogaopeng@njust.edu.cn.
Gaopeng
G
Zhao
School of Automation, Nanjing University of Science and Technology, Nanjing 210094, China. byming@njust.edu.cn.
Yuming
Y
Bo
point cloud; pose estimation; pose initial acquisition; pose tracking