Incremental low-discrepancy lattice methods for motion planning

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 3, Issue , 2003, Pages 2920-2927

  Lindemann, Stephen R ^a   LaValle, Steven M ^a  

^a University of Illinois at Urbana Champaign   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; ITERATIVE METHODS; PROBLEM SOLVING; RANDOM PROCESSES; SET THEORY;

LOW DISCREPANCY LATTICE METHOD; PSEUDORANDOM SEQUENCE; RECURSIVE ALGORITHMS;

MOTION PLANNING;

EID: 0344033888     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (20)

1. N. M. Amato and Y. Wu. A randomized roadmap method for path and manipulation planning. In IEEE Int. Conf. Robot. & Autom., pages 113-120, 1996.
2. R. Bohlin. Path planning in practice; lazy evaluation on a multi-resolution grid. In IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2001.
3. R. Bohlin and L. Kavraki. Path planning using lazy prm. In IEEE Int. Conf. Robot. & Autom., 2000.
4. V. Boor, N. H. Overmars, and A. F. van der Stappen. The gaussian sampling strategy for probabilistic roadmap planners. In IEEE Int. Conf. Robot. & Autom., pages 1018-1023, 1999.
5. M. Branicky, S. M. LaValle, K. Olsen, and L. Yang, Quasi-randomized path planning. In Proc. IEEE Int'l Conf. on Robotics and Automation, pages 1481-1487, 2001.
6. R. Geraerts and M. H. Overmars. A comparative study of probabilistic roadmap planners. In Proc. Workshop on the Algorithmic Foundations of Robotics (to appear), December 2002.
7. J. H. Halton. On the efficiency of certain quasirandom sequences of points in evaluating multi-dimensional integrals. Numer. Math., 2:84-90, 1960.
8. C. Holleman and L. E. Kavraki. A framework for using the workspace medial axis in PRM planners. In IEEE Int. Conf. Robot. & Autom., pages 1408-1413, 2000.
9. Y. K. Hwang and N. Ahuja. Gross motion planning-A survey. ACM Computing Surveys, 24(3):219-291, September 1992.
10. L. E. Kavraki, P. Svestka, J.-C. Latombe, and M. H. Overmars. Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Trans. Robot. & Autom., 12(4):566-580, June 1996.
11. S. M. LaValle and M. S. Branicky. On the relationship between classical grid search and probabilistic roadmaps. In Proc. Workshop on the Algorithmic Foundations of Robotics (to appear), December 2002.
12. J. Matousek. Geometric Discrepancy. Springer-Verlag, Berlin, 1999.
13. H. Niederreiter. Random Number Generation and Quasi-Monte-Carlo Methods. Society for Industrial and Appied Mathematics, Philadelphia, USA, 1992.
14. G. Sánchez and J.-C. Latombe. A single-query bi-directional probabilistic roadmap planner with lazy collision checking. In Int. Symp. Robotics Research, 2001.
15. T. Simeon, J.-P. Laumond., and C. Nissoux. Visibility based probabilistic roadmaps for motion planning. Advanced Robotics Journal, 14(6), 2000.
16. A. G. Sukharev. Optimal strategies of the search for an extremum. U.S.S.R. Computational Mathematics and Mathematical Physics, 11(4), 1971. Translated from Russian, Zh. Vychisl. Mat. i Mat. Fiz., 11, 4, 910-924, 1971.
17. J. G. van der Corput. Verteilungsfunktionen I. Akad. Wetensch., 38:813-821, 1935.
18. H. Weyl. Über die Gleichverteilung von Zahlen mod Eins. Math. Ann., 77:313-352, 1916.
19. S. A. Wilmarth, N. M. Amato, and P. F. Stiller. Maprm: A probabilistic roadmap planner with sampling on the medial axis of the free space. In IEEE Int. Conf. Robot. & Autom., pages 1024-1031, 1999.
20. Y. Yu and K. Gupta. On sensor-based roadmap: A framework for motion planning for a manipulator arm in unknown environments. In IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, pages 1919-1924, 1998.