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Multi-agent Data Fusion Architecture Proposal for Obtaining an Integrated Navigated Solution on UAV’s

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Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living (IWANN 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5518))

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Abstract

MAS have already more than proved their effectiveness while dealing with high level distributed problems, but some domains (usually low level ones) are still reluctant to their use, usually on a performance basis. UAV’s multisensor integration systems take information coming from different sensors and integrate them into one global positioning solution, with a pre-analyzed fixed data fusion architecture topology in a changing environment. In this paper we will propose a novel adaptative MAS data fusion architecture for this problem, able to change its topology according to its conditions, and thus effectively improving the overall quality of the system.

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References

  1. Carvalho, H.S., Heinzelman, W.B., Murphy, A.L., Coelho, C.J.N.: A General Data Fusion Architecture. In: Proceedings of the Sixth International Conference of Information Fusion. IEEE, Los Alamitos (2003)

    Google Scholar 

  2. Corchado, J.M., Molina, J.M.: Introducción a la teoría de agentes y sistemas multiagente. Catedral Publicaciones (2002)

    Google Scholar 

  3. Dickenson, L.: UAV’s on the Rise, Aviation Week and Space Technology. Aerospace Source Book 166(3) (January 2007)

    Google Scholar 

  4. Groves, P.D.: Principles of GNSS, Inertial, and Multisensor Integrated Navigation Systems. Artech House (2008)

    Google Scholar 

  5. Hegarty, C.J.: Least-Squares and Weighted Least-Squares Estmates. In: Kaplan, E.D., Hegarty, C.J. (eds.) Understanding GPS: Principles and Applications, 2nd edn., pp. 663–669. Artech House, Norwood (2006)

    Google Scholar 

  6. Kalman, R.E.: A new approach to linear filtering and prediction problems. Transaction of the ASME- Journal of Basic Engineering 82, 35–45 (1960)

    Article  Google Scholar 

  7. Kaplan, E.D., Hegarty, C.J. (eds.): Understanding GPS: Principles and Applications, 2nd edn. Artech House, Norwood (2006)

    Google Scholar 

  8. Kay, S.M.: Fundamentals of Statistical Processing. Prentice Hall Signal Processing Series, Estimation Theory, vol. I (April 1993)

    Google Scholar 

  9. Keith, D., Pannu, A., Sycara, K., Williamson, M.: Designing Behaviors for Information Agents. In: AUTONOMOUS AGENTS 1997, Proceedings of the First International Conference on Autonomous Agents, Marina del Rey CA, pp. 404–413. ACM Press, New York (1997)

    Google Scholar 

  10. Ladetto, Q., et al.: Digital Magnetic Compass and Gyroscope for Dismounted Soldier Position and Navigation. In: Proc. NATO RTO Symposium on Emerging Military Capabilities Enabled by Advances in Navigation Sensors, Istanbul, Turkey (October 2002)

    Google Scholar 

  11. OSD UAV Roadmap 2002-2007, Office of the Secretary of Defense (Acquisition, Technology and Logistics). Air Warfare (December 2002)

    Google Scholar 

  12. Pavón, J., Pérez, J.L.: Agentes software y sistemas multiagente. Pearson Educación, London (2004)

    Google Scholar 

  13. Rao, A.S., Georgeff, M.P.: Modeling Rational Agents within a BDI-Architecture. In: Second International Conference on Principles of Knowledge Representation and Reasoning (KR 1991), San Mateo, C.A. (1991)

    Google Scholar 

  14. Skog, I.: GNSS-aided INS for land vehicle positioning and navigation. Thesis for the degree of Licentiate of Engineering. KTH (Royal Institute of Engineering). Stockholm (2007)

    Google Scholar 

  15. Valavanis, K.P.: Advances in Unmanned Aerial Vehicles. State of the Art and the Road to Autonomy. International Series on Intelligent Systems, Control and Automation: Science and Engineering, vol. 33. Springer, Heidelberg (2007)

    Google Scholar 

  16. Welch, G., Bishop, G.: An introduction to the Kalman filter. University of North Carolina at Chapel Hill (2006)

    Google Scholar 

  17. Woodman, O.J.: An introduction to Inertial Navigation. Technical report 696. University of Cambridge (2007)

    Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Guerrero, J.L., García, J., Molina, J.M. (2009). Multi-agent Data Fusion Architecture Proposal for Obtaining an Integrated Navigated Solution on UAV’s. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_2

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  • DOI: https://doi.org/10.1007/978-3-642-02481-8_2

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02480-1

  • Online ISBN: 978-3-642-02481-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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