Skip to main content

Probabilistic path planning

  • Chapter
  • First Online:
Robot Motion Planning and Control

Part of the book series: Lecture Notes in Control and Information Sciences ((LNCIS,volume 229))

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J.M. Ahuactzin. Le Fil d'Ariadne: Une Méthode de Planification Générale. Application á la Planification Automatique de Trajectoires. PhD thesis, l'Institut National Polytechnique de Grenoble, Grenoble, France, September 1994.

    Google Scholar 

  2. R. Alami, F. Robert, F. Ingrand, and S. Suzuki. Multi-robot cooperation through incremental plan-merging. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 2573–2578, Nagoya, Japan, 1995.

    Google Scholar 

  3. J. Barraquand, L. Kavraki, J.-C. Latombe, T.-Y. Li, R. Motwani, and P. Raghavan. A random sampling scheme for path planning. To appear in Intern. Journal of Rob. Research.

    Google Scholar 

  4. J. Barraquand and J.-C. Latombe. A Monte-Carlo algorithm for path planning with many degrees of freedom. In Proc. IEEE Intern. Conf. on Robotics and Automation, pages 1712–1717, Cincinnati, OH, USA, 1990.

    Google Scholar 

  5. J. Barraquand and J.-C. Latombe. Robot motion planning: A distributed representation approach. Internat. Journal Robotics Research., 10(6):628–649, 1991.

    Google Scholar 

  6. J. Barraquand and J.-C. Latombe. Nonholonomic multibody mobile robots: Controllability and motion planning in the presence of obstacles. Algorithmica, 10:121–155, 1993.

    Google Scholar 

  7. P. Bessière, J.M. Ahuactzin, E.-G. Talbi, and E. Mazer. The Ariadne's clew algorithm: Global planning with local methods. In Proc. The First Workshop on the Algorithmic Foundations of Robotics, pages 39–47. A. K. Peters, Boston, MA, 1995.

    Google Scholar 

  8. S.J. Buckley. Fast motion planning for multiple moving robots. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 322–326, Scottsdale, Arizona, USA, 1989.

    Google Scholar 

  9. J.F. Canny. The Complexity of Robot Path Planning. MIT Press, Cambridge, USA, 1988.

    Google Scholar 

  10. M. Erdmann and T. Lozano-Pérez. On multiple moving objects. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1419–1424, San Francisco, CA, USA, 1986.

    Google Scholar 

  11. P. Ferbach. A method of progressive constraints for nonholonomic motion planning. Technical report, Electricité de France. SDM Dept., Chatou, France, September 1995.

    Google Scholar 

  12. C. Fernandes, L. Gurvits, and Z.X. Li. Optimal nonholonomic motion planning for a falling cat. In Z. Li and J.F. Canny, editors, Nonholonomic Motion Planning, Boston, USA, 1993. Kluwer Academic Publishers.

    Google Scholar 

  13. J. Hopcroft, J.T. Schwartz, and M. Sharir. On the complexity of motion planning for multiple independent objects; PSPACE-hardness of the warehouseman's problem. International Journal of Robotics Research, 3(4):76–88, 1984.

    Google Scholar 

  14. Th. Horsch, F. Schwarz, and H. Tolle. Motion planning for many degrees of freedom-random reflections at C-space obstacles. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 3318–3323, San Diego, USA, 1994.

    Google Scholar 

  15. Y. Hwang and N. Ahuja. Gross motion planning—a survey. ACM Comput. Surv., 24(3):219–291, 1992.

    Google Scholar 

  16. Y.K. Hwang and P.C. Chen. A heuristic and complete planner for the classical mover's problem. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 729–736, Nagoya, Japan, 1995.

    Google Scholar 

  17. B. Langlois J. Barraquand and J.-C. Latombe. Numerical potential field techniques for robot path planning. IEEE Trans. on Syst., Man., and Cybern., 22(2):224–241, 1992.

    Google Scholar 

  18. P. Jacobs, J.-P. Laumond, and M. Taïx. A complete iterative motion planner for a car-like robot. Journees Geometrie Algorithmique, 1990.

    Google Scholar 

  19. L. Kavraki, Random networks in configuration space for fast path planning. Ph.D. thesis, Department of Computer Science, Stanford University, Stanford, California, USA, January 1995.

    Google Scholar 

  20. L. Kavraki, M.N. Kolountzakis, and J.-C. Latombe. Analysis of probabilistic roadmaps for path planning. In IEEE International Conference on Robotics and Automation, pages 3020–3026, Minneapolis, MN, USA, 1996.

    Google Scholar 

  21. L. Kavraki and J.-C. Latombe. Randomized preprocessing of configuration space for fast path planning. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 2138–2145, San Diego, USA, 1994.

    Google Scholar 

  22. L. Kavraki, J.-C. Latombe, R. Motwani, and P. Raghavan. Randomized query processing in robot path planning. In Proc. 27th Annual ACM Symp. on Theory of Computing (STOC), pages 353–362, Las Vegas, NV, USA, 1995.

    Google Scholar 

  23. L. Kavraki, P. Švestka, J.-C. Latombe, and M.H. Overmars. Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Trans. Robot. Autom., 12:566–580, 1996.

    Google Scholar 

  24. F. Lamiraux and J.-P. Laumond. On the expected complexity of random path planning. In Proc. IEEE Intern. Conf. on Robotics and Automation, pages 3014–3019, Mineapolis, USA, 1996.

    Google Scholar 

  25. J.-C. Latombe. Robot Motion Planning. Kluwer Academic Publishers, Boston, USA, 1991.

    Google Scholar 

  26. J.-P. Laumond, P.E. Jacobs, M. Taïx, and R.M. Murray. A motion planner for nonholonomic mobile robots. IEEE Trans. Robot. Autom., 10(5), October 1994.

    Google Scholar 

  27. J.-P. Laumond, S. Sekhavat, and M. Vaisset. Collision-free motion planning for a nonholonomic mobile robot with trailers. In 4th IFAC Symp. on Robot Control, pages 171–177, Capri, Italy, September 1994.

    Google Scholar 

  28. J.-P. Laumond, M. Taïx, and P. Jacobs. A motion planner for car-like robots based on a mixed global/local approach. In IEEE IROS, July 1990.

    Google Scholar 

  29. Y.H. Liu, S. Kuroda, T. Naniwa, H. Noborio, and S. Arimoto. A practical algorithm for planning collision-free coordinated motion of multiple mobile robots. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1427–1432, Scottsdale, Arizona, USA, 1989.

    Google Scholar 

  30. P.A. O'Donnell and T. Lozano-Pérez. Deadlock-free and collision-free collision-free coordination of two robotic manipulators. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 484–489, Scottsdale, Arizona, USA, 1989.

    Google Scholar 

  31. M.H. Overmars. A random approach to motion planning. Technical Report RUU-CS-92-32, Dept. Comput. Sci., Utrecht Univ., Utrecht, the Netherlands, October 1992.

    Google Scholar 

  32. M.H. Overmars and P. Švestka. A probabilistic learning approach to motion planning. In Proc. The First Workshop on the Algorithmic Foundations of Robotics, pages 19–37. A. K. Peters, Boston, MA, 1994.

    Google Scholar 

  33. P. Pignon. Structuration de l'Espace pour une Planification Hiérarchisée des Trajectoires de Robots Mobiles. Ph.D. thesis, LAAS-CNRS and Université Paul Sabatier de Toulouse, Toulouse, France, 1993. Report LAAS No. 93395 (in French).

    Google Scholar 

  34. J.A. Reeds and R.A. Shepp. Optimal paths for a car that goes both forward and backward. Pacific Journal of Mathematics, 145(2):367–393, 1991.

    Google Scholar 

  35. J.H. Reif and M. Sharir. Motion planning in the presence of moving obstacles. In Proc. 25th IEEE Symp. on Foundations of Computer Science, pages 144–154, 1985.

    Google Scholar 

  36. J.T. Schwartz and M. Sharir. Efficient motion planning algorithms in environments of bounded local complexity. Report 164, Dept. Comput. Sci., Courant Inst. Math. Sci., New York Univ., New York, NY, 1985.

    Google Scholar 

  37. J.T. Schwartz and M. Sharir. On the ‘piano movers’ problem: III. coordinating the motion of several independent bodies: The special case of circular bodies moving amidst polygonal obstacles. International Journal of Robotics Research, 2(3):46–75, 1983.

    Google Scholar 

  38. S. Sekhavat and J.-P. Laumond. Topological property of trajectories computed from sinusoidal inputs for nonholonomic chained form systems. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 3383–3388, April 1996.

    Google Scholar 

  39. S. Sekhavat, P. Švestka, J.-P. Laumond, and M.H. Overmars. Probabilistic path planning for tractor-trailer robots. Technical Report 96007, LAAS-CNRS, Toulouse, France, 1995.

    Google Scholar 

  40. S. Sekhavat, P. Švestka, J.-P. Laumond, and M.H. Overmars. Multi-level path planning for nonholonomic robots using semi-holonomic subsystems. To appear in Intern. Journal of Rob Research.

    Google Scholar 

  41. M. Sharir and S. Sifrony. Coordinated motion planning for two independent robots. In Proceedings of the Fourth ACM Symposium on Computational Geometry, 1988.

    Google Scholar 

  42. P. Souères and J.-P. Laumond. Shortest paths synthesis for a car-like robot. IEEE Trans. Automatic Control, 41:672–688, 1996.

    Google Scholar 

  43. H.J. Sussmann. Lie brackets, real analyticity and geometric control. In R.W. Brockett, R.S. Millman, and H.J. Sussmann, editors, Differential Geometric Control Theory. Birkhauser, 1983.

    Google Scholar 

  44. H.J. Sussmann. A general theorem on local controllability. SIAM Journal on Control and Optimization, 25(1):158–194, January 1987.

    Google Scholar 

  45. P. Švestka. A probabilistic approach to motion planning for car-like robots. Technical Report RUU-CS-93-18, Dept. Comput. Sci., Utrecht Univ., Utrecht, the Netherlands, April 1993.

    Google Scholar 

  46. P. Švestka and M.H. Overmars. Coordinated motion planning for multiple car-like robots using probabilistic roadmaps. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 1631–1636, Nagoya, Japan, 1995.

    Google Scholar 

  47. P. Švestka and M.H. Overmars. Motion planning for car-like robots using a probabilistic learning approach. Intern. Journal of Rob Research, 16:119–143, 1995.

    Google Scholar 

  48. P. Švestka and M.H. Overmars. Multi-robot path planning with super-graphs. In Proc. CESA '96 IMACS Multiconference, Lille, France, July 1996.

    Google Scholar 

  49. P. Švestka and J. Vleugels. Exact motion planning for tractor-trailer robots. In Proc. IEEE Internat. Conf. on Robotics and Automation, pages 2445–2450, Nagoya, Japan, 1995.

    Google Scholar 

  50. D. Tilbury, R. Murray, and S. Sastry. Trajectory generation for the n-trailer problem using goursat normal form. In Proc. IEEE Internat. Conf. on Decision and Control, San Antonio, Texas, 1993.

    Google Scholar 

  51. P. Tournassoud. A strategy for obstacle avoidance and its application to multirobot systems. In Proceedings of the IEEE International Conference on Robotics and Automation, pages 1224–1229, San Francisco, CA, USA, 1986.

    Google Scholar 

  52. S.M. La Valle and S.A. Hutchinson. Multiple-robot motion planning under independent objectives. To appear in IEEE Trans. Robot. Autom..

    Google Scholar 

  53. F. van der Stappen. Motion Planning amidst Fat Obstacles. Ph.D. thesis, Dept. Comput. Sci., Utrecht Univ., Utrecht, the Netherlands, October 1994.

    Google Scholar 

  54. F. van der Stappen, D. Halperin, and M.H. Overmars. The complexity of the free space for a robot moving amidst fat obstacles. Comput. Geom. Theory Appl., 3:353–373, 1993.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

J. -P. Laumond

Rights and permissions

Reprints and permissions

Copyright information

© 1998 Springer-Verlag London Limited

About this chapter

Cite this chapter

Švestka, P., Overmars, M.H. (1998). Probabilistic path planning. In: Laumond, J.P. (eds) Robot Motion Planning and Control. Lecture Notes in Control and Information Sciences, vol 229. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0036074

Download citation

  • DOI: https://doi.org/10.1007/BFb0036074

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76219-5

  • Online ISBN: 978-3-540-40917-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics