Least squares-based data fusion strategies and robotic applications

Richard O. Eason*, Sei ichiro Kamata

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


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
Pages (from-to)566-573
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - 1991 Jan 1
Externally publishedYes
EventSensor Fusion III: 3-D Perception and Recognition - Boston, MA, USA
Duration: 1990 Nov 51990 Nov 8

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering


Dive into the research topics of 'Least squares-based data fusion strategies and robotic applications'. Together they form a unique fingerprint.

Cite this