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Proceedings Paper

Least-squares-based data fusion strategies and robotic applications
Author(s): Richard O. Eason; Sei-ichiro Kamata
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Paper Abstract

Many approaches to data fusion involve the use of least squares methods. Such methods are typically used for parameter estimation in applications such as pose estimation, motion analysis, shape estimation, and camera calibration. In this paper we describe the general least squares problem and some common solution methods, and overview its use in several robotic applications.

Paper Details

Date Published: 1 April 1991
PDF: 8 pages
Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25295
Show Author Affiliations
Richard O. Eason, Univ. of Maine (United States)
Sei-ichiro Kamata, Univ. of Maine (United States)

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

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