Journal of information and communication convergence engineering

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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Kinodynamic Motion Planning with Artificial Wavefront Propagation

  • Ogay, Dmitriy (Department of Computer Science& Engineering, Graduate School, Korea University of Technology and Education) ;
  • Kim, Eun-Gyung (School of Computer Science& Engineering, Korea University of Technology and Education)
  • Received : 2013.09.06
  • Accepted : 2013.11.08
  • Published : 2013.12.31
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Abstract

In this study, we consider the challenges in motion planning for automated driving systems. Most of the existing online motion-planning algorithms, which take dynamics into account, find it difficult to operate in an environment with narrow passages. Some of the existing algorithms overcome this by offline preprocessing if environment is known. In this work an online algorithm for motion planning with dynamics in an unknown cluttered environment with narrow passages is presented. It utilizes an idea of hybrid planning with sampling- and discretization-based motion planners, which run simultaneously in a full configuration space and a derived reduced space. The proposed algorithm has been implemented and tested with a real autonomous vehicle. It provides significant improvements in computational time performance over basic planning algorithms and allows the generation of smoother paths than those generated by the recently developed hybrid motion planners.

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References

  1. E. Plaku, L. E. Kavraki, and M. Y. Vardi, "Motion planning with dynamics by a synergistic combination of layers of planning," IEEE Transactions on Robotics, vol. 26, no. 3, pp. 469-482, 2010. https://doi.org/10.1109/TRO.2010.2047820
  2. I. A. Sucan and L. E. Kavraki, "Kinodynamic motion planning by interior-exterior cell exploration," in Algorithmic Foundation of Robotics VIII. Heidelberg, Germany: Springer, pp. 449-464, 2009.
  3. E. Rimon and D. E. Koditschek, "Exact robot navigation using artificial potential functions," IEEE Transactions on Robotics and Automation, vol. 8, no. 5, pp. 501-518, 1992. https://doi.org/10.1109/70.163777
  4. D. S. Yershov and S. M. LaValle, "Simplicial Dijkstra and A* algorithms for optimal feedback planning," in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, San Francisco: CA, pp. 3862-3867, 2011.
  5. J. A. Sethian, Level Set Methods and Fast Marching Methods, 2nd ed. New York, NY: Cambridge University Press, 1999.
  6. D. Dolgov, S. Thrun, M. Montemerlo, and J. Diebel, "Practical search techniques in path planning for autonomous driving," in Proceedings of the 1st International Symposium on Search Techniques in Artificial Intelligence and Robotics, Chicago: IL, 2008.
  7. D. Ferguson, T. M. Howard, and M. Likhachev, "Motion planning in urban environments," Journal of Field Robotics, vol. 25, no. 11- 12, pp. 939-960, 2008. https://doi.org/10.1002/rob.20265
  8. S. M. LaValle and J. J. Kuffner, "Randomized kinodynamic planning," International Journal of Robotics Research, vol. 20, no. 5, pp. 378-400, 2001. https://doi.org/10.1177/02783640122067453
  9. L. Kavraki, P. Svestka, J. C. Latombe, and M. H. Overmars, "Probabilistic roadmaps for path planning in high-dimensional configuration spaces," IEEE Transactions on Robotics and Automation, vol. 12, no. 4, pp. 566-580, 1996. https://doi.org/10.1109/70.508439
  10. S. Dalibard and J. P. Laumond, "Control of probabilistic diffusion in motion planning," in Algorithmic Foundation of Robotics VIII. Heidelberg, Germany: Springer, pp. 467-481, 2009.
  11. S. Rodriguez, X. Tang, J. M. Lien, and N. M. Amato, "An obstacle-based rapidly-exploring random tree," in Proceedings of the IEEE International Conference on Robotics and Automation, Orlando: FL, pp. 895-900, 2006.
  12. S. Karaman and E. Frazzoli, "Sampling-based algorithms for optimal motion planning," International Journal of Robotics Research, vol. 30, no. 7, pp. 846-894, 2011. https://doi.org/10.1177/0278364911406761