Pose Measurement and Motion Estimation of Space Non-Cooperative Targets Based on Laser Radar and Stereo-Vision Fusion

Abstract

The pose (position and attitude) measurement of space non-cooperative targets is one of the key technologies in on-orbit service. Traditional stereo-vision-based methods are easily affected by illumination conditions, while the 3D laser radar has a good stability, but the point cloud is sparse. In this paper, a method based on the 3D laser radar and stereo-vision information is proposed to measure the pose and estimate the motion for non-cooperative targets. The proposed method can not only adapt to the harsh lighting conditions, but also has better robustness and higher precision. First, find the matching point corresponding to the binocular camera by using the stereo matching algorithm, and then, calculate the 3D coordinates of the matching points according to the least squares method. Combined with the fusion calibration result, the point cloud data acquired by the 3D laser radar is converted to the left camera frame. Second, integrate the point cloud data obtained by the above two sensors to obtain a complete point cloud model of the non-cooperative target. Third, the obtained point cloud model is registered, and the rigid transformation matrix of two adjacent point clouds is solved. Then, the relative pose and velocity (linear velocity and angular velocity) of the non-cooperative target are estimated by the extended Kalman filter (EKF) algorithm. Finally, an experimental system was built. It consists of a UR5 robot, a satellite mockup, two cameras, a 3D laser radar, and an API laser tracker (for evaluating the accuracy of measurement), was built. The experiment results verified the proposed method.