DOI QR코드

DOI QR Code

Introduction to Autonomous Vehicle PHAROS

자율주행자동차 PHAROS

  • Ryu, Jee-Hwan (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Park, Jang-Sik (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Ogay, Dmitriy (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Bulavintsev, Segey (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Kim, Hyuk (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Song, Young-wook (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Yoon, Moon-Young (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Kim, Jea-Seok (School of Mechanical Engineering, Korea University of Technology and Education) ;
  • Kang, Jeon-Jin (School of Mechanical Engineering, Korea University of Technology and Education)
  • 유지환 (한국기술교육대학교 기계정보공학부) ;
  • 박장식 (한국기술교육대학교) ;
  • ;
  • ;
  • 김혁 (한국기술교육대학교 기계공학부) ;
  • 송영욱 (한국기술교육대학교 기계공학부) ;
  • 윤문영 (한국기술교육대학교 기계공학부) ;
  • 김재석 (한국기술교육대학교 기계공학부) ;
  • 강전진 (한국기술교육대학교 기계공학부)
  • Received : 2011.12.05
  • Accepted : 2012.06.27
  • Published : 2012.08.01

Abstract

This paper introduces the autonomous vehicle Pharos, which participated in the 2010 Autonomous Vehicle Competition organized by Hyundai-Kia motors. PHAROS was developed for high-speed on/off-road unmanned driving avoiding diverse patterns of obstacles. For the high speed traveling up to 60 km/h, long range terrain perception, real-time path planning and high speed vehicle motion control algorithms are developed. This paper describes the major hardware and software components of our vehicle.

Keywords

References

  1. M. Buehler, K. Iagnemma, S. Singh, The 2005 DARPA Grand Challenge: the Great Robot Race, Springer Trats in Advnaced Robotics 36, Springer-verlag, Berlin; 2007.
  2. A. Elfes, "Using occupancy grids for mobile robot perception and navigation," Computer, vol 22, no. 6, pp. 46-57, 1989.
  3. D. Dolgov, S. Thrun, M. Montemerlo, and J. Diebel. "Practical search techniques in path planning for autonomous driving," in Proceedings of the First International Symposium on Search Techniques in Artificial Intelligence and Robotics, 2008.
  4. E. Frazzoli, M. A. Dahleh, and E. Feron, "Real-time motion planning for agile autonomous vehicles," AIAA Journal of Guidance and Control, vol. 25, no. 1, pp. 116-129, 2002. https://doi.org/10.2514/2.4856
  5. A. Kelly, A Partial Analysis of the High Speed Autonomous Navigation Problem, Project report of "Perception for outdoor navigation" and "Unmanned Ground Vehicle System," Carnegie Mellon University, 1994.
  6. Y. Kuwata, G. A. Fiore, J. Teo, E. Frazzoli, and J. P. How, "Motion planning for urban driving using RRT," in Proc. IROS, pp. 1681- 1686, 2008.
  7. 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
  8. S. Thrun and et al., "Stanley: The Robot that Won the DARPA Grand Challenge," Journal of Field Robotics, vol. 23, no. 9, pp. 661-692, 2006. https://doi.org/10.1002/rob.20147
  9. C. Urmson and et al., "A robust approach to high-speed navigation for unrehearsed desert terrain," Journal of Field Robotics, vol. 23, no. 8, pp. 427-508, 2006.
  10. C. Urmson and et al., "Autonomous driving in urban environments: Boss and the Urban Challenge," Journal of Field Robotics, vol. 25, no. 8, pp. 425-466, 2008. https://doi.org/10.1002/rob.20255
  11. http://www.hyundai-ngv.com/techcontest/, in Korean