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12 March 2024 A long-distance 6D pose estimation system for space object recognition using region-scanning LiDAR
Yoon-Seop Lim, Seok-Jun An, Sung-Hyun Lee, Yong-Hwa Park
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Proceedings Volume 12899, MOEMS and Miniaturized Systems XXIII; 128990A (2024) https://doi.org/10.1117/12.3000456
Event: SPIE OPTO, 2024, San Francisco, California, United States
Abstract
In this paper, a novel 6-Dimensional (3 positions and 3 orientations) pose estimation system using indirect Time-of- Flight (ToF) region-scanning LiDAR is proposed for long-distance space object recognition. Specifically, the targeted space object detection algorithm with an IR amplitude image, and 6D pose estimation algorithm with high-resolution 3D data are performed with the region-scanning LiDAR. The proposed system is verified with a self-collected dataset of space objects in space simulation environments. The proposed pose estimation algorithm shows a maximum position error of 1% and orientation error of 5° in robust experiment conditions. Moreover, the proposed system outperformed the other conventional space object 6D pose estimation system with previous depth sensors in terms of the detection rates and 6D pose accuracy at long distances.
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(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Yoon-Seop Lim, Seok-Jun An, Sung-Hyun Lee, and Yong-Hwa Park "A long-distance 6D pose estimation system for space object recognition using region-scanning LiDAR", Proc. SPIE 12899, MOEMS and Miniaturized Systems XXIII, 128990A (12 March 2024); https://doi.org/10.1117/12.3000456
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KEYWORDS
Pose estimation
LIDAR
3D image processing
3D acquisition
Data acquisition
Sensors
Distance measurement
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