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Comparison of Data Fusion Techniques for Robot Navigation

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Advances in Artificial Intelligence (SETN 2006)

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

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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.

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References

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

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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
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  2. Antonios Gasteratos
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  3. Angelos Amanatiadis
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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

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© 2006 Springer-Verlag Berlin Heidelberg

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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

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  • 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)

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