An essential component of In-Space Servicing, Assembly, and Manufacturing (ISAM) is the tracking of objects within the visual range of a satellite. One particularly common and available form of small satellites, the CubeSat, is used extensively in orbit and may be included in ISAM applications. CubeSats use a standard format of one or multiple 10cm cubes. Tracking the orientation of these CubeSats with range sensors as they move and tumble comes with challenges, as they are feature-sparse, being made of identically sized boxes. The proposed method combines a camera image stream with the use of Light Detecting and Ranging (LiDAR) sensors to get an estimate of the states of a CubeSat. An image recognition algorithm is used to determine which CubeSat face is which from the image stream, then the cloud of 3D points from the LiDAR will be used to measure the normal vectors of those faces for orientation estimation. Experimental measurements of the estimation system were performed with one CubeSat face pointing between 0 and 60 degrees relative to the LiDAR vector with rotations at 10-degree intervals in two body axes. Average orientation error is less than 1.5 degrees and maximum orientation error at the extreme angles of a single face are less than 3 degrees with standard deviation less than 1 degree averaged over all cases. This sensor-fusion approach does not include the use of fiducial markers.
Pose estimation of a 3D tumbling CubeSat using a camera and LiDAR sensor-fusion approach
Sensors and Systems for Space Applications XVIII ; 2025 ; Orlando, Florida, United States
Proc. SPIE ; 13483
21.05.2025
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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