On comparing statistical and set-based methods in sensor data fusion

Gregory D. Hager, Sean P. Engelson, Sami Atiya

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

Abstract

We compare the theoretical and practical considerations of two common sensor data fusion methodologies: set-based and statistically based parameter estimation. We first examine their convergence behavior for a variety of simulated problems. We then describe robot localization systems implemented using both methods and compare their performance. Our conclusion is that set-based methods have performance that sometimes exceeds that of statistical methods, although this result is highly problem dependent. We then characterize these problem dependencies.

Original languageEnglish (US)
Title of host publicationProceedings - IEEE International Conference on Robotics and Automation
PublisherPubl by IEEE
Pages352-358
Number of pages7
ISBN (Print)0818634529
StatePublished - Jan 1 1993
Externally publishedYes
EventProceedings of the IEEE International Conference on Robotics and Automation - Atlanta, GA, USA
Duration: May 2 1993May 6 1993

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2
ISSN (Print)1050-4729

Other

OtherProceedings of the IEEE International Conference on Robotics and Automation
CityAtlanta, GA, USA
Period5/2/935/6/93

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering

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  • Cite this

    Hager, G. D., Engelson, S. P., & Atiya, S. (1993). On comparing statistical and set-based methods in sensor data fusion. In Proceedings - IEEE International Conference on Robotics and Automation (pp. 352-358). (Proceedings - IEEE International Conference on Robotics and Automation; Vol. 2). Publ by IEEE.