Advertisement

Sensor-based Trajectory Deformation: Application to Reactive Navigation of Nonholonomic Robots

  • Florent Lamiraux
  • Olivier Lefebvre
Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 401)

Abstract

In this chapter, we present a sensor-based trajectory deformation process for nonholonomic robots. The method is based on infinitesimal perturbations of the input functions of the current trajectory. Input perturbation is computed in such a way that a an objective function decreases and that the trajectory initial and final configurations are kept unchanged. The method is then extended to docking for wheeled mobile robots. The final configuration of the deformation process is moved to a configuration in order to make perception fit a docking pattern. The method is demonstrated on mobile robot Hilare 2 towing a trailer.

Keywords

Mobile Robot Motion Planning Nonholonomic System Nonholonomic Constraint Dynamic Control System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Barraquand, J., Latombe, J.C.: Robot motion planning: A distributed representation approach. International Journal on Robotics Research 10(6), 628–649 (1991)CrossRefGoogle Scholar
  2. 2.
    Brock, O., Khatib, O.: Real-time replanning in high dimensional configuration spaces using sets of homotopic paths. In: International Conference on Robotics and Automation, pp. 550–555. IEEE, San Francisco (2000)Google Scholar
  3. 3.
    Divelbiss, A., Wen, J.: A path space approach to nonholonomic motion planning in the presence of obstacles. IEEE Transactions on Robotics and Automation 13(3), 443–451 (1997)CrossRefGoogle Scholar
  4. 4.
    Fernandes, C., Gurvits, L., Li, Z.: Optimal Nonholonomic Motion Planning for a Falling Cat. In: Nonholonomic Motion Planning, pp. 379–421. Kluwer Academic Press, Dordrecht (1993)Google Scholar
  5. 5.
    Fiorini, P., Shiller, Z.: Motion planning in dynamic environments using velocity obstacles. International Journal on Robotics Research 17(7), 760–772 (1998)CrossRefGoogle Scholar
  6. 6.
    Khatib, M., Jaouni, H., Chatila, R., Laumond, J.P.: Dynamic path modification for car-like nonholonomic mobile robots. In: International Conference on Robotics and Automation, pp. 2920–2925. IEEE, Albuquerque (1997)Google Scholar
  7. 7.
    Khatib, O.: Real-time obstacle avoidance for manipulators and mobile robots. International Journal on Robotics Research 5(1), 90–98 (1986)CrossRefMathSciNetGoogle Scholar
  8. 8.
    Lamiraux, F., Bonnafous, D., Lefebvre, O.: Reactive path deformation for nonholonomic mobile robots. IEEE Transactions on Robotics 20(6), 967–977 (2004)CrossRefGoogle Scholar
  9. 9.
    Lamiraux, F., Sekhavat, S., Laumond, J.P.: Motion planning and control for hilare pulling a trailer. IEEE Transactions on Robotics and Automation 15(4), 640–652 (1999)CrossRefGoogle Scholar
  10. 10.
    Large, F., Sekhavat, S., Shiller, Z., Laugier, C.: Toward real-time global motion planning in a dynamic environment using the nlvo concept. In: International Conference on Intelligent Robots and Systems, pp. 607–612. IEEE/RSJ, Lausanne (2002)Google Scholar
  11. 11.
    Laumond, J.P.: Controllability of a multibody mobile robot. IEEE Transactions on Robotics and Automation 9(6), 755–763 (1993)CrossRefGoogle Scholar
  12. 12.
    Laumond, J.P., Sekhavat, S., Lamiraux, F.: Guidelines in Nonholonomic Motion Planning for Mobile Robots. In: Robot Motion Planning and Control. LNCIS, pp. 2–53. Springer, NY (1998)CrossRefGoogle Scholar
  13. 13.
    LaValle, S.M., Kuffner, J.J.: Randomized kinodynamic planning. International Journal of Robotics Research 20(5), 378–400 (2001)CrossRefGoogle Scholar
  14. 14.
    Lefebvre, O., Lamiraux, F.: Docking task for nonholonomic mobile robots. In: International Conference on Robotics and Automation, Orlando, USA, pp. 3736–3741 (2006)Google Scholar
  15. 15.
    Maxim Likhachev, D.F.: Planning long dynamically-feasible maneuvers for autonomous vehicles. In: Proceedings of Robotics: Science and Systems IV, Zurich, Switzerland (2008)Google Scholar
  16. 16.
    Murray, R.M., Sastry, S.: Steering nonholonomic systems using sinusoids. In: Conference on Decision and Control, pp. 2097–2101. IEEE, Los Alamitos (1990)CrossRefGoogle Scholar
  17. 17.
    Quinlan, S., Khatib, O.: Elastic bands: Connecting path planning and control. In: International Conference on Robotics and Automation, pp. 802–807. IEEE, Atlanta (1993)Google Scholar
  18. 18.
    Rimon, E., Koditschek, D.: Exact robot navigation using artificial potential functions. IEEE Transactions on Robotics and Automation 8, 501–518 (1992)CrossRefGoogle Scholar
  19. 19.
    Švestka, P., Overmars, M.: Coordinated motion planning for multiple car-like robots using probabilistic roadmaps. In: Proc. IEEE Int. Conf. Robotics and Automation, Japan, pp. 1631–1636 (1995)Google Scholar
  20. 20.
    Švestka, P., Overmars, M.: Probabilistic path planning. In: Laumond, J.P. (ed.) Robot Motion Planning and Control. LNCIS, pp. 255–304. Springer, NY (1998)CrossRefGoogle Scholar

Copyright information

© Springer London 2010

Authors and Affiliations

  • Florent Lamiraux
    • 1
  • Olivier Lefebvre
    • 1
  1. 1.LAAS-CNRSToulouseFrance

Personalised recommendations