PARTICLE-FILTER APPROACH AND MOTION STRATEGY FOR COOPERATIVE LOCALIZATION

Alberto Vale, Fernando Gomez Bravo, Maria Isabel Ribeiro

Abstract

This paper proposes a Particle-Filter approach and a set of motion strategies to cooperatively localize a team of three robots. The allocated mission consists on the path following of a closed trajectory and obstacle avoidance in isolated and unstructured scenarios. The localization methodology required for the correct path following relies on distance and orientation measurements among the robots and the robots and a fixed active beacon. Simulation results are presented.

References

  1. Barsky, B. (1987). Computer graphics and geometric modelling using ß-Splines . S.-Verlag.
  2. Betke, M. and Gurvits, L. (1997). Mobile robot localization using landmarks. IEEE Transaction on Robotics and Automation, 13(2):251 - 263.
  3. Cuesta, F. and Ollero, A. (2005). Intelligent Mobile Robot Navigation. Springer.
  4. Cuesta, F., Ollero, A., Arrue, B., and Braunstingl, R. (2003). Intelligent control of nonholonomic mobile robots with fuzzy perception. Fuzzy Set and Systems, 134:47 - 64.
  5. Ge, S. S. and Fua, C.-H. (2005). Complete multi-robot coverage of unknown environments with minimum repeated coverage. Proc. of the 2005 IEEE ICRA, pages 727 - 732.
  6. Grabowski, R. and Khosla, P. (2001). Localization techniques for a team of small robots. Proc. of the IEEE/RSJ Int. Conf. on Intelligent Robots and Systems, 2:1067 - 1072.
  7. Grewal, M. S. and Andrews, A. P. (1993). Kalman Filtering Theory and Practice. Prentice-Hall, Englewood Cliffs and New Jersey.
  8. Gustavi, T., Hu, X., and Karasalo, M. (2005). Multi-robot formation control and terrain servoing with limited sensor information. Preprints of the 16th IFAC World Congress.
  9. Martinelli, A., Pont, F., and Siegwart, R. (2005). Multirobot localization using relative observations. Proc. of the 2005 IEEE Int. Conf. on Robotics and Automation, pages 2808 - 2813.
  10. Navarro-Serment, L. E., Grabowski, R., Paredis, C., and Khosla, P. (2002). Localization techniques for a team of small robots. IEEE Rob. and Aut. Magazine, 9:31 - 40.
  11. Rekleitis, I. (2004). A particle filter tutorial for mobile robot localization. (TR-CIM-04-02).
  12. Tang, K. W. and Jarvis, R. A. (2004). An evolutionary computing approach to generating useful and robust robot team behaviours. Proc. of 2004 IEEE/RSJ IROS, 2:2081 - 2086.
  13. Thrun, S., Fox, D., Burgard, W., and Murphy, F. D. (2001). Robust monte carlo localization for mobile robot. Artificial Intelligence Magazine, 128(1 - 2):99 - 141.
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Paper Citation


in Harvard Style

Gomez Bravo F., Vale A. and Isabel Ribeiro M. (2006). PARTICLE-FILTER APPROACH AND MOTION STRATEGY FOR COOPERATIVE LOCALIZATION . In Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO, ISBN 978-972-8865-60-3, pages 50-57. DOI: 10.5220/0001203300500057


in Bibtex Style

@conference{icinco06,
author={Fernando Gomez Bravo and Alberto Vale and Maria Isabel Ribeiro},
title={PARTICLE-FILTER APPROACH AND MOTION STRATEGY FOR COOPERATIVE LOCALIZATION},
booktitle={Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,},
year={2006},
pages={50-57},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001203300500057},
isbn={978-972-8865-60-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Third International Conference on Informatics in Control, Automation and Robotics - Volume 2: ICINCO,
TI - PARTICLE-FILTER APPROACH AND MOTION STRATEGY FOR COOPERATIVE LOCALIZATION
SN - 978-972-8865-60-3
AU - Gomez Bravo F.
AU - Vale A.
AU - Isabel Ribeiro M.
PY - 2006
SP - 50
EP - 57
DO - 10.5220/0001203300500057