Space debris pose and motion identification using 4D LiDAR.
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| Title: | Space debris pose and motion identification using 4D LiDAR. |
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| Authors: | Li, Jun Yang1 (AUTHOR) junyang.li@mail.utoronto.ca, Wolfe, Sean1 (AUTHOR) sean.wolfe@mail.utoronto.ca, Emami, M. Reza1 (AUTHOR) reza.emami@utoronto.ca |
| Source: | Advances in Space Research. Aug2026, Vol. 78 Issue 4, p3807-3829. 23p. |
| Subjects: | Space debris, Pose estimation (Computer vision), Monte Carlo method, Optical sensors, Orbital rendezvous (Space flight), LIDAR, Kalman filtering, Motion analysis |
| Abstract: | • Complete pose and motion estimation for non-cooperative space debris is proposed. • A consensus-based algorithm enables a single optical sensor to determine debris states. • A commercial off-the-shelf 4D LiDAR is verified for close-range rendezvous. • Monte Carlo simulations demonstrate robustness and computational efficiency. Determining the pose and motion of an uncooperative object, such as space debris, during close-range rendezvous requires a real-time, comprehensive perception suite. However, resource constraints, especially on miniaturized platforms, may prohibit the use of conventional optical payloads with computationally intensive algorithms. In this paper, a framework for the application of a 4D LiDAR, providing both range and velocity measurements, is presented. The proposed pose and motion estimation framework consists of a concord-based iterated sigmapoint Kalman filter. Two distinct oriented bounding boxes are constructed, with their principal axes aligned with vectors obtained from the eigenvectors using principal component analysis and plane identification by random sample consensus, respectively. While individually, neither bounding box can accurately match the ground truth pose of the debris, the agreement between the two bounding box orientations as an input measurement to the sigmapoint Kalman filter allows the filter to reject poor measurements and perform orientation estimation. Through Monte Carlo simulations, it is shown that the filter is capable of leveraging both the speed and range measurements of the 4D LiDAR, in order to reliably and accurately determine the full pose and motion of a space debris in real-time. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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