REAL TIME TRACKING OF AN OMNIDIRECTIONAL ROBOT - An Extended Kalman Filter Approach

José Gonçalves, José Lima, Paulo Costa

Abstract

This paper describes a robust localization system, similar to the used by the teams participating in the Robocup Small size league (SLL). The system, developed in Object Pascal, allows real time localization and control of an autonomous omnidirectional mobile robot. The localization algorithm is done resorting to odometry and global vision data fusion, applying an extended Kalman filter, being this method a standard approach for reducing the error in a least squares sense, using measurements from different sources.

References

  1. (2008). Robocup. http://www.robocup.org/.
  2. Borestein, Everett, and Feng (1996). where am I, Sensores and Methods for Mobile Robot Positioning. Prepared by the University of Michigan.
  3. Choset, H., Lynch, K., Hutchinson, S., Kantor, G., Burgard, W., Kavraki, L., and Thrun, S. (2005). Principles of Robot Motion : Theory, Algorithms, and Implementations. MIT Press.
  4. Dudek, G. and Jenkin, M. (2000). Computational Principles of Mobile Robotics. Cambridge University Press.
  5. Gonc¸alves, J., Costa, P., and Moreira, A. (2005). Controlo e estimac¸ a˜o do posicionamento absoluto de um robot omnidireccional de treˆs rodas. Revista Robótica, Nr 60, pp 18-24.
  6. Gonc¸alves, J., Pinheiro, P., Lima, J., and Costa, P. (2007). Tutorial introdutório para as competic¸o˜es de futebol robótico. IEEE RITA - Latin American Learning Technologies Journal, 2(2):63-72.
  7. Kalmár-Nagy, T., D'Andrea, R., and Ganguly, P. (2002). Near-optimal dynamic trajectory generation and control of an omnidirectional vehicle. In Sibley School of Mechanical and Aerospace Engineering.
  8. Negenborn, R. (2003). Robot Localization and Kalman Filters - On finding your position in a noisy world. Master Thesis, Utrecht University.
  9. Ribeiro, F., Moutinho, I., Silva, P., Fraga, C., and Pereira, N. (2004). Controlling omni-directional wheels of a robocup msl autonomous mobile robot. In Proceedings of the Scientific Meeting of the Robotics Portuguese Open.
  10. Ribeiro, M. I. (2004). Gaussian Probability Density Functions: Properties and Error Characterization. Technical Report, IST.
  11. Sousa, A. (2003). Arquitecturas de Sistemas Rob óticos e Localizac¸ a˜o em Tempo Real Através de Visa˜o. PHD Thesis, Faculty of Engineering of the University of Porto.
  12. Thrun, S., Burgard, W., and Fox, D. (2005). Probabilistic robotics. MIT Press.
  13. Welch, G. and Bishop, G. (2001). An introduction to the Kalman filter. Technical Report, University of North Carolina at Chapel Hill.
Download


Paper Citation


in Harvard Style

Gonçalves J., Lima J. and Costa P. (2008). REAL TIME TRACKING OF AN OMNIDIRECTIONAL ROBOT - An Extended Kalman Filter Approach . In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 978-989-8111-31-9, pages 5-10. DOI: 10.5220/0001474500050010


in Bibtex Style

@conference{icinco08,
author={José Gonçalves and José Lima and Paulo Costa},
title={REAL TIME TRACKING OF AN OMNIDIRECTIONAL ROBOT - An Extended Kalman Filter Approach},
booktitle={Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2008},
pages={5-10},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001474500050010},
isbn={978-989-8111-31-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - REAL TIME TRACKING OF AN OMNIDIRECTIONAL ROBOT - An Extended Kalman Filter Approach
SN - 978-989-8111-31-9
AU - Gonçalves J.
AU - Lima J.
AU - Costa P.
PY - 2008
SP - 5
EP - 10
DO - 10.5220/0001474500050010