Abstract
The relative pose estimation between the chaser and the non-cooperative target is a significant prerequisite for performing on-orbit servicing (OOS) missions. The chaser could design the close-range rendezvous trajectory to approach the non-cooperative target only when the relative pose parameters are obtained effectively and efficiently. In this paper, a pose estimation scheme is designed to obtain the relative pose parameters between the chaser and the non-cooperative target coated with multilayer insulation material (MLI). The scheme utilizes a time-of-flight (TOF) camera to acquire 3D point clouds of the non-cooperative target, and uses the iterative closest point (ICP) method to achieve the point cloud registration between every two frames. Aiming at decreasing the non-systematic errors caused by MLI in the data acquisition of the TOF camera, the corresponding point median filtering approach is adopted to filter out the bad corresponding point pairs generated in the ICP method. A semi-physical experiment is carried out to evaluate the performance of the proposed scheme, the result of which shows that the proposed scheme could notably improve the accuracy of pose estimation of the non-cooperative target, meanwhile the computational efficiency is also ensured.
Highlights
Today, more than 100 million artificial objects move in Earth orbits [1]
This paper studies the relative pose estimation problem between the chaser and the band coating non-cooperative
000 1 in which x1, y1 and z1 represent the relative position between the TOF camera and the non-cooperative target at the initial moment, and they are assumed as known parameters in this paper
Summary
More than 100 million artificial objects move in Earth orbits [1]. Many non-cooperative targets, including malfunctioning spacecraft, scrapped satellites and garbage debris, may threaten the safety of proper functioning spacecraft, and occupy the Earth orbits and waste space resources. When the TOF camera is calculating the depth data of an area of a non-cooperative target surface, the uneven areas around it could be regarded as some other nearby objects, which will introduce light scattering errors. 000 1 in which x1, y1 and z1 represent the relative position between the TOF camera and the non-cooperative target at the initial moment, and they are assumed as known parameters in this paper. Assuming that the i-th frame 3D point cloud of the noncooperative target acquired by the TOF camera is Pi, the pose estimation process of the non-cooperative target can be described as follows. The point cloud registration method is used to register Pi and P1 in the reference coordinate system to obtain the transformation matrix Hi1 of OiS−xSi yiSziS respect to O1S−xS1y1Sz1S, Hi of OiS − xSi yiSziS respect to OT − xTyTzT can be obtained by
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
