Least-squares-based data fusion strategies and robotic applications

Richard O. Eason; Sei-ichiro Kamata

doi:10.1117/12.25295

1 April 1991 Least-squares-based data fusion strategies and robotic applications

Richard O. Eason, Sei-ichiro Kamata

Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991) https://doi.org/10.1117/12.25295
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States

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.

Citation Download Citation

Richard O. Eason and Sei-ichiro Kamata "Least-squares-based data fusion strategies and robotic applications", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); https://doi.org/10.1117/12.25295

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