HOW TO TACKLE SENSOR-BASED MANIPULATOR PLANNING PROBLEMS USING MODEL-BASED PLANNERS: CONVERSION AND IMPLEMENTATION

D. Um

References

  1. [1] V. Lumelsky, Algorithmic and complexity issues of robot motion in an uncertain environment, Journal of Complexity, 3(2), 1987, 146–182.
  2. [2] A. Sankaranarayanan & M. Vidyasager, A new path planning algorithm for moving a point object amidst unknown obstacles in a plane, in Proc. of the IEEE Int. Conf. on Robotics & Automation, Cincinnati OH, May 1990, 1936–1939.
  3. [3] H. Noborio, R. Nom, & S. Hirao, A new sensor-based path-planning algorithm whose path length is shorter on the average, in Proc. of the IEEE Int. Conf. on Robotics & Automation, 3, New Orleans, LA, April 2004, 2832–2839.
  4. [4] E. Cheung & V. Lumelsky, A sensitive skin system for motion control of robot arm manipulators, Robotics and autonomous systems, 10(1), 1992, 9–32.
  5. [5] K. Sun & V. Lumelsky, Path planning among unknown obstacles: the case of a three-dimensional Cartesian arm, IEEE Trans. on Robotics and Automation, 8(6), December 1992, 776–786.
  6. [6] D. Um, B. Stankovich, K. Giles, T. Hammond, & V. Lumelsky, A modularized sensitive skin for motion planning in uncertain environments, in Proc. of the IEEE Int. Conf. on Robotics & Automation, Leuven, Belgium, May 1998, 7–12.
  7. [7] V. Lumelsky, S.M. Shur, & S. Wagner, Sensitive skin, IEEE Sensor Journal, 1(1), June 2001, 41–51.
  8. [8] T. Simeon, J.-P. Laumond, & C. Nixxoux, Visibility based probabilistic roadmaps for motion planning, Advanced robotics Journal, 14(6), 2000, 477–494.
  9. [9] N.M. Amato & Y. Wu, A randomized roadmap method for path and manipulation planning, In Proc. of the IEEE Int. Conf. on Robotics & Automation, Minneapolis, MN, 1996, 113–120.
  10. [10] S.M. Lavalle & M.S. Branicky, “On the relationship between classical grid search and probabilistic roadmaps, The International Journal of Robotics Research, 23(7–8), 2004, 673–692.
  11. [11] L. Kavraki & J.-C. Latombe, Randomized preprocessing of configuration space for fast path planning, in Proc. of the IEEE Int. Conf. on Robotics & Automation, San Diego, May 1994, 2138–2145.
  12. [12] V. Boor, M.H. Overmars, & A.F. Van der Stappen, The Gaussian sampling strategy for probabilistic roadmap planners. in Proc. of the IEEE Int. Conf. on Robotics & Automation, Detroit Michigan, 1999, 1018–1023.
  13. [13] S. Wilmath, N.M. Amato, & P. Stiller, MAPRM: A probabilistic roadmap planner with sampling on the medial axis of the free space. in Proc. of the IEEE Int. Conf. on Robotics & Automation, Detroit Michigan, 1999, 1024–1031.
  14. [14] D. Hsu, L.E. Kavraki, J.-C. Latombe, R. Motwani, & S. Sorkin, in Proceedings of the third workshop on the algorithmic foundations of robotics on Robotics : the algorithmic perspective: the algorithmic perspective table of contents, Houston, Texas, United States (Natick, MA: A. K. Peters, Ltd., 1998), 141–153.
  15. [15] J. Schwartz & M. Sharir, On the piano movers’ problem: III, Coordinating the motion of several independent bodies. The special case of circular bodies moving amidst polygonal barriers. The International Journal of Robotics Research, 2(3), 1983, 46–74.
  16. [16] M. Mehrandezh & K.K. Gupta, Simultaneous path planning and free space exploration with skin sensor, in Proc. of the IEEE Int. Conf. on Robotics & Automation, Washington DC, May 2002, 3838–3843.
  17. [17] J. Lee, & H. Choset, Sensor-based planning for a rod-shaped robot in three dimensions: Piecewise retracts of R∩3 × S∩2, International Journal of Robotics Research, 24(5), May 2005, 343–383.
  18. [18] G. Oriolo, M. Vendittelli, L. Fredam, & G. Troso, The SRT method: randomized strategies for exploration, in Proc. of the IEEE Int. Conf. on Robotics & Automation, New Orleans, LA, April 2004, 4688–4694.
  19. [19] S.M.L. Valle & J. Kuffner, Rapidly-exploring random trees: Progress and prospects in B.R. Donald, K.M. Lynch & D. Rus (Eds.), Algorithmic and Computational Robotics: New Directions (WAFR 2000), A.K. Peters, Boston, 2001, 293–308.
  20. [20] G. Sanchez & J.-C. Latombe, A single-query bi-directional probabilistic roadmap planner with lazy collision checking, International Symposium on Robotics Research: planning and modeling, Lorne, Victoria, Australia, 2001, 403–417.
  21. [21] R. Bohlin & L. Kavraki, Path planning using lazy PRM in Proc. of the IEEE Int. Conf. on Robotics & Automation, 2000.
  22. [22] J.-C. Latombe, Robot Motion Planning (Springer Publishers, New York, 1991).
  23. [23] D. Um, Sensor based randomized lattice diffusion planner for unknown environment manipulation, In Proc. of the IEEE Int. Conf. on Intelligent Robots and Systems, Beijing, China, 2006, 5382–5387.
  24. [24] A.M. Shkel & V. Lumelsky, The jogger’s problem: control of dynamics in real-time motion planning, Journal of IFAC, 33(7), 1997, 1219–1233.
  25. [25] M. Kalisiak, & M. van de Panne, RRT-blossom: RRT with a local flood-fill behavior, in Proc. of the IEEE Int. Conf. on Robotics & Automation, Orlando, FL, May 2006, 1237–1242.
  26. [26] D. Um, infrared photometry for 2D proximity sensing and 3D geometry visualization, Journal of engineering and technology, 1, 2007, 10–17.
  27. [27] L. Zhang & D. Manocha, An efficient retraction-based RRT planner, in Proc. of the IEEE Int. Conf. on Robotics & Automation, Pasadena, CA, May 2008, 3743–3750.

Important Links:

Go Back