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Proceedings Paper

Pose determination of spinning satellites using tracks of novel regions
Author(s): Andrew John Lee; David P. Casasent
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Paper Abstract

An algorithm for using time sequence video data from a single camera to determine position and orientation (pose) of spin stabilized satellites with respect to a robotic spacecraft is discussed. The system utilizes novelty detection and filtering for locating novel parts and a neural net to track these parts over time. The present paper addresses the estimation of pose from the tracks of the novel regions. The path traced out by a given part (or region) is approximately elliptical in image space, and a psuedoinverse technique is used to find a best-fit ellipse for a set of track points. The position, shape, and orientation of the ellipse are functions of the satellite geometry and its pose. Using this ellipse, and information from a model of the given satellite, an iterative technique is used to perturb an initial guess of pose such that the error between the best-fit ellipse and a predicted ellipse is minimized. Results of using this algorithm on sequences of images of a satellite at various poses and under various lighting conditions are presented.

Paper Details

Date Published: 1 April 1991
PDF: 12 pages
Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25246
Show Author Affiliations
Andrew John Lee, Carnegie Mellon Univ. (United States)
David P. Casasent, Carnegie Mellon Univ. (United States)

Published in SPIE Proceedings Vol. 1383:
Sensor Fusion III: 3D Perception and Recognition
Paul S. Schenker, Editor(s)

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