• Documents
  • Authors
  • Tables
  • Log in
  • Sign up
  • MetaCart
  • DMCA
  • Donate

CiteSeerX logo

Advanced Search Include Citations
Advanced Search Include Citations

DMCA

Adapting the Sample Size in Particle Filters Through KLD-Sampling (2003)

Cached

  • Download as a PDF

Download Links

  • [www.cs.washington.edu]
  • [www.cs.utexas.edu]
  • [www.cs.utexas.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [www.cs.washington.edu]
  • [mobilerobotics.cs.washington.edu]
  • [rse-lab.cs.washington.edu]

  • Other Repositories/Bibliography

  • DBLP
  • Save to List
  • Add to Collection
  • Correct Errors
  • Monitor Changes
by Dieter Fox
Venue:International Journal of Robotics Research
Citations:150 - 9 self
  • Summary
  • Citations
  • Active Bibliography
  • Co-citation
  • Clustered Documents
  • Version History

BibTeX

@ARTICLE{Fox03adaptingthe,
    author = {Dieter Fox},
    title = {Adapting the Sample Size in Particle Filters Through KLD-Sampling},
    journal = {International Journal of Robotics Research},
    year = {2003},
    volume = {22},
    pages = {2003}
}

Share

Facebook Twitter Reddit Bibsonomy

OpenURL

 

Abstract

Over the last years, particle filters have been applied with great success to a variety of state estimation problems. In this paper we present a statistical approach to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation process.

Keyphrases

particle filter    sample size    statistical approach    sample set    great success    estimation process    state estimation problem    last year   

Powered by: Apache Solr
  • About CiteSeerX
  • Submit and Index Documents
  • Privacy Policy
  • Help
  • Data
  • Source
  • Contact Us

Developed at and hosted by The College of Information Sciences and Technology

© 2007-2019 The Pennsylvania State University