Skip to main content
SpringerLink
Log in

Comparison of Data Fusion Techniques for Robot Navigation

  • Conference paper
Advances in Artificial Intelligence (SETN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3955))

Included in the following conference series:

Abstract

This paper proposes and compares several data fusion techniques for robot navigation. The fusion techniques investigated here are several topologies of the Kalman filter. The problem that had been simulated is the navigation of a robot carrying two sensors, one Global Positioning System (GPS) and one Inertial Navigation System (INS). For each of the above topologies, the statistic error and its, mean value, variance and standard deviation were examined.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Hall, D.L., Llinas, J.: Handbook of Multisensor Data Fusion. CRC Press, Boca Raton (2001)

    Google Scholar 

  2. Johnson, R., Sasiadek, J., Zalewski, J.: Kalman Filter Enhancement for UAV Navigation. In: Proc. SCS 2003 CollaborativeaTechnologies Symposium, Orlando, FL (2003)

    Google Scholar 

  3. Kalman, R.E., Bucy, R.: New Results in Linear Filtering and Prediction Theory. Journal of Basic Engineering 83, 95–108 (1961)

    Article  MathSciNet  Google Scholar 

  4. Maybeck, P.S.: The Kalman Filter: An Introduction to Concepts. Springer, New York (1990)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Production and Management Engineering, Greece

    Nikolaos Kyriakoulis & Antonios Gasteratos

  2. Department of Electrical and Computer Engineering, School of Engineering, Democritus University of Thrace, GR-671 00, Xanthi, Greece

    Angelos Amanatiadis

Authors
  1. Nikolaos Kyriakoulis
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonios Gasteratos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Angelos Amanatiadis
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Computer Science Department of University of Crete, Greece

    Grigoris Antoniou

  2. Institute of Computer Science, Foundation for Research & Technology – Hellas (FORTH), Vassilika Vouton, P.O. Box 1385, 71110, Heraklion, Greece

    George Potamias

  3. Institute of Informatics and Telecommunications, NCSR "Demokritos", 15310 A., Paraskevi Attikis, Greece

    Costas Spyropoulos

  4. Institute of Computer Science, FO.R.T.H., Vassilika Vouton, P.O. Box 1385, GR 71110, Heraklion, Greece

    Dimitris Plexousakis

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Kyriakoulis, N., Gasteratos, A., Amanatiadis, A. (2006). Comparison of Data Fusion Techniques for Robot Navigation. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_65

Download citation

  • DOI: https://doi.org/10.1007/11752912_65

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34117-8

  • Online ISBN: 978-3-540-34118-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation