DOI QR코드

DOI QR Code

New Path Planning Algorithm based on the Visibility Checking using a Quad-tree on a Quantized Space, and its improvements

격자화된 공간상에서 4중-나무 구조를 이용한 가시성 검사를 바탕으로 한 새로운 경로 계획 알고리즘과 그 개선 방안들

  • 김정태 (포항공과대학교 컴퓨터공학과, 생체인식연구센터) ;
  • 김대진 (포항공과대학교 컴퓨터공학과, 생체인식연구센터)
  • Published : 2010.01.01

Abstract

In this paper, we introduce a new path planning algorithm which combines the merits of a visibility graph algorithm and an adaptive cell decomposition. We quantize a given map with empty cells, blocked cells, and mixed cells, then find the optimal path on the quantized map using a visibility graph algorithm. For reducing the number of the quantized cells we use the quad-tree technique which is used in an adaptive cell decomposition, and for improving the performance of the visibility checking in making a visibility graph we propose a new visibility checking method which uses the property of the quad-tree instead of the well-known rotational sweep-line algorithm. For the more efficient visibility checking, we propose two additional improvements for our suggested method. Both of them are used for reducing the visited cells in the quad-tree. The experiments for a performance comparison of our algorithm with other well-known algorithms show that our proposed method is superior to others.

Keywords

References

  1. H. Choset, K. M. Lynch, S. Hutchinson, G. Kantor, W. Burgard, L. E. Kavraki, and S. Thrun, Principles of Robot Motion: Theory, Algorithms and Implementations. Cambridge, MA, USA: MIT Press, 2005.
  2. J. C. Latombe, Robot Motion Planning, Kluwer Academic, Boston, 1991.
  3. R. Siegwart and I. R. Nourbakhsh, Introduction to autonomous mobile robot, Cambridge, MA, USA: MIT Press, 2004.
  4. S. Thrun, W. Burgard, and D. Fox, Probabilistic robotics, Cambridge, MA, USA: MIT Press, 2005.
  5. V. J. Lumelsky and A. A. Stepanov, "Path planning strategies for a point mobile automaton moving amidst unknown obstacles of arbitrary shape," Algorithmica, 2:403-430, 1987. https://doi.org/10.1007/BF01840369
  6. I. Kamon and E. Rivlin, "Sensory-based motion planning with global proofs," IEEE Transactions on Robotics and Automation, 13(6):814-822, Dec. 1997. https://doi.org/10.1109/70.650160
  7. S. L. Iaubach and J. W. Burdick, "RoverBug: Long range navigation for mars rovers," Lecture Notes in Control and Information Sciences, pp. 339-348, 1999.
  8. J. Borenstein and Y. Koren, "The vector field histogram - fast obstacle avoidance for mobile robots," IEEE Journal of Robotics and Automation, vol. 7, no. 3, pp. 279-288, Jun. 1991.
  9. R. V. Benson, Euclidean Geometry and Convexity. New York: McGrew-Hill, 1966.
  10. H. Choset, "Incremental construction of the generalized Voronoi diagram," in Proc. of the 1st CGC Workshop on Computationol Geometry, Oct. 1997.
  11. L. Guibas, L. Ramshaw, and J. Stolfi, "A kinetic framework for computational geometry," Foundations of Computer Science, 1983., 24th Annual Symposium on, pp. 100-111, Nov. 1983.
  12. H. Choset, "Incremental construction of the generalized Voronoi diagram, the generalized Voronoi graph, and the hierarchical generalized Voronoi graph," in Proc. Of the 1st CGC Workshop on Computational Geometry, Oct. 1997.
  13. H. Choset, S. Walker, K. Eiamsa.-Ard, and J. Burdick, "Sensor-based exploration: Incremental construction of the hierarchical generalized Voronoi graph," The Int. Journal of Robotics Research, vol. 19, pp. 96-125, Feb. 2000. https://doi.org/10.1177/02783640022066770
  14. J. Barraquand and J. C. Latombe, "Robot motion planning: A distributed representation approach," The Int. Journal of Robotics Research, vol. 10, pp. 628-649, 1991. https://doi.org/10.1177/027836499101000604
  15. O. Khatib, "Real-time obstacle avoidance for manipulators and mobile robots," Robotics and Automation, in Proc. 1985 IEEE Int. Conf. on, vol. 2, pp. 500-505, Mar. 1985. https://doi.org/10.1109/ROBOT.1985.1087247
  16. R. Volpe and P. Khosla, "Artificial potentials with elliptical isopotential contours for obstacle avoidance," Decision and Control, 26th IEEE Conf. on, vol. 26. pp. 180-185, Dec. 1987.
  17. J. Barraquand, L. E. Kavraki, J. C. Latombe, T. Y. Li, R. Motwani, and P. Raghavan, "A random sampling scheme for robot path planning," The Int. Journal of Robotics Research, vol. 17, no. 6, pp. 759-774, 1997.
  18. K.-Y. Im and S.-Y. Oh, "An extended virtual force field based behavioral fusion with neural networks and evolutionary programming for mobile robot navigation," Evolutionary Computation, proc of the 2000 Congress on, vol. 2, pp. 1238-1244, 2000.
  19. L. E. Kavraki, J. C. Latombe, and M. H. Overmars, "Probabilistic roadmaps for path planning in high-dimensional configuration spaces," in IEEE Int. Conf. on Methods and Models in Automation and Robotics, pp. 566-580, Morgan Kaufmann, 1997.
  20. M. H. Overmars and P. Svestka, "A probabilistic learning approach to motion planning," in Proc. Workshop on Algorithmic Foundation of Robotics, pp. 19-38, 1994.
  21. N. Nilsson, "A mobile automation: An application of artificial intelligence techniques," Tech. Reports 40, AI Center, SRI International, 333 Ravenswood Ave, Menlo Park, CA 94025, Mar. 1969.
  22. D.-T. Lee, "Proximity and reachability in the plane," Ph.D. thesis, Campaign, IL. USA. 1978.
  23. T. H. Cormen, C. E. Leiserson, R. L. Rivest, and C. Stein, Introduction to algorithms, second edition, Cambridge, MA, USA: MIT Press, 2001.
  24. 김정태, 김대진, "가시성 그래프와 가변-셀-분할을 이용한 새로운 경로계획," in Proc. of Korea Computer Congress(KCC), vol. 36, no. 1, pp. 357-361, 2009.
  25. 김정태, 김대진, "가시성 그래프와 가변-셀-분할을 이용한 경로계획 알고리즘," 한국 자동 제어학술회의 (KACC 2009), pp. 283-288, 2009.
  26. M. de Berg, O. Cheong, M. van Kreveld, and M. H. Overmars, Computational Geometry: Algorithms and Applications. Heidelberg: Springer-Verlag, 2008.

Cited by

  1. Expanded Douglas–Peucker Polygonal Approximation and Opposite Angle-Based Exact Cell Decomposition for Path Planning with Curvilinear Obstacles vol.9, pp.4, 2019, https://doi.org/10.3390/app9040638