Satellite articulation sensing using computer vision
Document Type
Conference Proceeding
Publication Date
1-5-2017
Abstract
Autonomous on-orbit satellite servicing benefits from an inspector satellite that can gain as much information as possible about the primary satellite. This includes performance of articulated objects such as solar arrays, antennas, and sensors. This paper presents a method of sensing and characterizing single-axis articulation of a solar panel on a target satellite from an inspector satellite in a natural circumnavigation trajectory around the target. The method presented uses trajectories of feature points on the target satellite to sense articulated motion. Motion segmentation is then used to separate feature points into groups consisting only of points that undergo the same motion. Structure from motion methods are used to develop point clouds representing each of the distinct objects. Finally, the axis and angle of the articulation are identified. The method is demonstrated using simulated data where point cloud radial error on the order of 2%, articulation axis error of approximately 0.04 radians, and relative articulation angle mean square error of approximately 0.002 radians were obtained.
Source Publication
55th AIAA Aerospace Sciences Meeting
Recommended Citation
Curtis, D. H., & Cobb, R. G. (2017, January). Satellite articulation sensing using computer vision. 55th AIAA Aerospace Sciences Meeting. https://doi.org/10.2514/6.2017-1329
Comments
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Author note: David Curtis was an AFIT PhD student at the time of this conference. (AFIT-ENY-DS-18-S-060, September 2018.)