PARTIAL MOTION PLANNING FRAMEWORK FOR REACTIVE PLANNING WITHIN DYNAMIC ENVIRONMENTS

Stéphane PETTI, Thierry FRAICHARD

Abstract

This paper addresses the problem of motion planning in dynamic environments. As dynamic environments impose a real-time constraint, the planner has a limited time only to compute a motion. Given the intrinsic complexity of motion planning, computing a complete motion to the goal within the time available is, in many real-life situations, impossible to achieve. Partial Motion Planning (PMP) is the answer proposed in this paper to this problem. PMP calculates a motion until the time available is over. At each iteration step, PMP returns the best partial motion to the goal computed so far. Like reactive decision scheme, PMP faces a safety issue: what guarantee is there that the system will never end up in a critical situations yielding an inevitable collision? In this paper the safety issue relies upon the concept of Inevitable Collision States that account for both the system dynamics and the moving obstacles. By computing ICS-free partial motion, the system safety can be guaranteed. Application of PMP to the case of a car-like system in a dynamic environment is presented.

References

  1. Borenstein, J. and Koren, Y. (1991). The vector field histogram - fast obstacle avoidance for mobile robots. IEEE Journal of Robotics and Automation, 7(3):278- 288.
  2. Brock, O. and Khatib, O. (2000). Real time replanning in high-dimensional configuration spaces using sets of homotopic paths. In Proc. IEEE Intl. Conf. on Robotics and Automation, San Francisco (US).
  3. Bruce, J. and Veloso, M. (2002). Real-time randomized path planning for robot navigation. In Int. Conf. on Intelligent Robots and Systems, Lausanne, Switzerland.
  4. Canny, J. (1988). The complexity of Robot Motion Planning. MIT Press, Cambridge, MA.
  5. Feron, E., Frazzoli, E., and Dahleh, M. (2000). Real-time motion planning for agile autonomous vehicles. In AIAA Conference on Guidance, Navigation and Control, Denver (US).
  6. Fiorini, P. and Shiller, Z. (1998). Motion planning in dynamic environments using velocity obstacles. International Journal of Robotics Research, 17(7):760-772.
  7. Fox, D., Burgard, W., and Thrun, S. (1995). The dynamic window approach to collision avoidance. Technical Report IAI-TR-95-13.
  8. Fraichard, T. and Asama, H. (2004). Inevitable collision states - a step towards safer robots? Advanced Robotics, 18(10):1001-1024.
  9. Fraichard, T. and Laugier, C. (1992). Kinodynamic planning in a structured and time-varying 2D workspace. In Int. Conf. on Robotics and Automation, Nice, (FR).
  10. Hsu, D., Kindel, R., Latombe, J.-C., and Rock, S. (2002). Randomized kinodynamic motion planning with moving obstacles. Int. Journal of Robotics Research, 21(3):233-255.
  11. Kavraki, L., Svestka, P., Latombe, J.-C., and Overmars, M. H. (1996). Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Transactions on Robotics and Automation, 12:566- 580.
  12. Khatib, M. (1996). Sensor-based motion control for mobile robots. PhD thesis, LAAS-CNRS December, 1996.
  13. LaValle, S. and Kuffner, J. (1999). Randomized kinodynamic planning. In Int. Conf. on Robotics and Automation, pages 473-479, Detroit (US).
  14. Minguez, J., Montano, L., and Santos-Victor, J. (2002). Reactive navigation for non-holonomic robots using the ego kinematic space. In Int. Conf. on Robotics and Automation, Washington (US).
  15. Simmons, R. (1996). The curvature velocity method for local obstacle avoidance. In International Conference on Robotics and Automation, pages 3375-3382, Minneapolis (USA).
  16. Stentz, A. (1995). The focussed D* algorithm for real-time replanning. In Int. Joint Conf. on Artificial Intelligence, pages 1652-1659, Montreal, Quebec.
  17. Vasquez, D. and Fraichard, T. (2004). Motion prediction for moving objects: a statistical approach. In Int. Conf. on Robotics and Automation, New Orleans, LA.
  18. Wang, C.-C., Thorpe, C., and Thrun, S. (2003). Online simultaneous localization and mapping with detection and tracking of moving objects: Theory and results from a ground vehicle in crowded urban areas. In IEEE Int. Conf. on Robotics and Automation, Taipei, Taiwan.
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Paper Citation


in Harvard Style

PETTI S. and FRAICHARD T. (2005). PARTIAL MOTION PLANNING FRAMEWORK FOR REACTIVE PLANNING WITHIN DYNAMIC ENVIRONMENTS . In Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO, ISBN 972-8865-30-9, pages 199-204. DOI: 10.5220/0001185401990204


in Bibtex Style

@conference{icinco05,
author={Stéphane PETTI and Thierry FRAICHARD},
title={PARTIAL MOTION PLANNING FRAMEWORK FOR REACTIVE PLANNING WITHIN DYNAMIC ENVIRONMENTS},
booktitle={Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,},
year={2005},
pages={199-204},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001185401990204},
isbn={972-8865-30-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Second International Conference on Informatics in Control, Automation and Robotics - Volume 4: ICINCO,
TI - PARTIAL MOTION PLANNING FRAMEWORK FOR REACTIVE PLANNING WITHIN DYNAMIC ENVIRONMENTS
SN - 972-8865-30-9
AU - PETTI S.
AU - FRAICHARD T.
PY - 2005
SP - 199
EP - 204
DO - 10.5220/0001185401990204