An obstacle-based rapidly-exploring random tree

Proceedings - IEEE International Conference on Robotics and Automation

Volumn 2006, Issue , 2006, Pages 895-900

  Rodríguez, Samuel ^a   Tang, Xinyu ^a   Lien, Jyh Ming ^a   Amato, Nancy M ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICULATED ROBOTS; C-SPACE INFORMATION; RAPIDLY-EXPLORING RANDOM TREE (RRT); TREE-BASED PATH PLANNERS;

ALGORITHMS; INFORMATION ANALYSIS; MOBILE ROBOTS; PROBLEM SOLVING; TREES (MATHEMATICS);

MOTION PLANNING;

EID: 33845643186     PISSN: 10504729     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ROBOT.2006.1641823     Document Type: Conference Paper

References (25)

1. N. M. Amato, O. B. Bayazit, L. K. Dale, C. V. Jones, and D. Vallejo. OBPRM: An obstacle-based PRM for 3D workspaces. In Robotics: The Algorithmic Perspective, pages 155-168, Natick, MA, 1998.
2. A.K. Peters. Proceedings of the Third Workshop on the Algorithmic Foundations of Robotics (WAFR), Houston, TX, 1998.
3. N. M. Amato, O. B. Bayazit, L. K. Dale, C. V. Jones, and D. Vallejo. Choosing good distance metrics and local planners for probabilistic roadmap methods. IEEE Trans. Robot. Automat., 16(4):442-447, August 2000.
4. Preliminary version appeared in ICRA 1998, pp. 630-637.
5. J. Barraquand and J. C. Latombe. Robot motion planning: A distributed representation approach. Int. J. Robot. Res., 10(6):628-649, 1991.
6. O. B. Bayazit, G. Song, and N. M. Amato. Enhancing randomized motion planners: Exploring with haptic hints. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 529-536, 2000.
7. J. Berg and M. Overmars. Using workspace information as a guid to non-uniform sampling in probabilistic roadmap planners. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 453-460, 2004.
8. P. Bessiere, J. M. Ahuactzin, E. G. Talbi, and E. Mazer. The Ariadne's clew algorithm: Global planning with local methods. In Proc. IEEE Int. Conf. Intel. Rob. Syst. (IROS), volume 2, pages 1373-1380, 1993.
9. V. Boor, M. H. Overmars, and A. F. van der Stappen. The Gaussian sampling strategy for probabilistic roadmap planners. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), volume 2, pages 1018-1023, 1999.
10. H. Chang and T. Y. Li. Assembly maintainability study with motion planning. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 1012-1019, 1995.
11. D. Hsu, T. Jiang, J. Reif, and Z. Sun. Bridge test for sampling narrow passages with proabilistic roadmap planners. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 4420-4426, 2003.
12. D. Hsu, L. E. Kavraki, J.-C. Latombe, R. Motwani, and S. Sorkin. On finding narrow passages with probabilistic roadmap planners. In Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR), pages 141-153, 1998.
13. D. Hsu, J.-C. Latombe, and R. Motwani. Path planning in expansive configuration spaces. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 2719-2726, 1997.
14. L. Kavraki and J. C. Latombe. Randomized preprocessing of configuration space for fast path planning. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 2138-2145, 1994.
15. 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. Automat., 12(4):566-580, August 1996.
16. J. J. Kuffner and S. M. LaValle. RRT-Connect: An Efficient Approach to Single-Query Path Planning. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 995-1001, 2000.
17. S. M. LaValle and J. J. Kuffner. Rapidly-Exploring Random Trees: Progress and Prospects. In Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR), pages SA45-SA59, 2000.
18. J.-M. Lien, O. B. Bayazit, R.-T. Sowell, S. Rodriguez, and N. M. Amato. Shepherding behaviors. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 4159-4164, April 2004.
19. M. Morales, L. Tapia, R. Pearce, S. Rodriguez, and N. M. Amato. A machine learning approach for feature-sensitive motion planning. In Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR), pages 316-376, Utrecht/Zeist, The Netherlands, July 2004.
20. M. Overmars and P. Svestka. A probabilistic learning approach to motion planning. In Proc. Int. Workshop on Algorithmic Foundations of Robotics (WAFR), pages 19-37, 1994.
21. E. Plaku, K. E. Bekris, B. Y. Chen, A. M. Ladd, and L. E. Kavraki. Sampling-based roadmap of trees for parallel motion planning. IEEE Trans. Robot. Automat., 2005.
22. S. Redon and M. C. Lin. Practical local planning in the contact space. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), April 2005.
23. J. H. Reif. Complexity of the mover's problem and generalizations. In Proc. IEEE Symp. Foundations of Computer Science (FOCS), pages 421-427, San Juan, Puerto Rico, October 1979.
24. 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 Proc. IEEE Int. Conf. Robot. Autom. (ICRA), volume 2, pages 1024-1031, 1999.
25. A. Yershova, L. Jaillet, T. Simeon, and S. M. Lavalle. C-space subdivision and integration in feature-sensitive motion planning. In Proc. IEEE Int. Conf. Robot. Autom. (ICRA), pages 3867-3872, April 2005.