Least squares-based data fusion strategies and robotic applications

Richard O. Eason, Seiichiro Kamata

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsPaul S. Schenker
PublisherPubl by Int Soc for Optical Engineering
Pages566-573
Number of pages8
Volume1383
Publication statusPublished - 1991
Externally publishedYes
EventSensor Fusion III: 3-D Perception and Recognition - Boston, MA, USA
Duration: 1990 Nov 51990 Nov 8

Other

OtherSensor Fusion III: 3-D Perception and Recognition
CityBoston, MA, USA
Period90/11/590/11/8

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ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Eason, R. O., & Kamata, S. (1991). Least squares-based data fusion strategies and robotic applications. In P. S. Schenker (Ed.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 1383, pp. 566-573). Publ by Int Soc for Optical Engineering.