제어로봇시스템학회논문지 (Journal of Institute of Control, Robotics and Systems)

  • 제17권9호
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  • Pages.902-907
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  • 2011
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  • 1976-5622(pISSN)
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  • 2233-4335(eISSN)
제어로봇시스템학회 (Institute of Control, Robotics and Systems)
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영상 교시기반 주행 알고리듬 성능 평가

Performance Evaluation of Visual Path Following Algorithm

  • 최이삭 (서울과학기술대학교 NID융합기술대학원) ;
  • 하종은 (서울과학기술대학교 자동차공학과)
  • Choi, I-Sak (Seoul National University of Science and Technology) ;
  • Ha, Jong-Eun (Seoul National University of Science and Technology)
  • 투고 : 2011.04.18
  • 심사 : 2011.07.20
  • 발행 : 2011.09.01
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초록

In this paper, we deal with performance evaluation of visual path following using 2D and 3D information. Visual path follow first teaches driving path by selecting milestone images then follows the same route by comparing the milestone image and current image. We follow the visual path following algorithm of [8] and [10]. In [8], a robot navigated with 2D image information only. But in [10], local 3D geometries are reconstructed between the milestone images in order to achieve fast feature prediction which allows the recovery from tracking failures. Experimental results including diverse indoor cases show performance of each algorithm.

키워드

참고문헌

  1. C. Urmson, "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
  2. M. Montemerlo, S. Thrun, D. Koller, and B. Wegbreit, "FastSLAM: A factored solution to the simultaneous localization and mapping problem," Proc. of the AAAI National Conference on Artificial Intelligence, 2002.
  3. S. Thrun, W. Burgard, and D. Fox, Probabilistic Robotics, MIT Press, 2006.
  4. R. Sim, P. Elinas, M. Griffin, A. Shyr, and J. J. Little, "Design and analysis of a framework for real-time vision-based SLAM using Rao-Blackwellised particle filters," Proceedings of the 3rd Canadian Conference on Computer and Robot Vision (CRV'06), 2006.
  5. S. Se, D. Lowe, and J. Little, "Mobile robot localization and mapping with uncertainty using scale-invariant visual landmarks," The International Journal of Robotics Research, vol. 21, no. 8, pp. 735-758, 2002. https://doi.org/10.1177/027836402761412467
  6. A. J. Davision, I. D. Reid, N. D. Molton, and O. Stasse, "MonoSLAM: Real-time single camera SLAM," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 26, no. 6, pp. 1052-1067, 2007. https://doi.org/10.1109/TPAMI.2007.1049
  7. N. Karlsson, E. D. Bernardo, J. Ostrowski, L. Goncalves, P. Pirjanian, and M. E. Munich, "The vSLAM algorithm for robust localization and mapping," IEEE International Conference on Robotics and Automation, pp. 24-29, 2005. https://doi.org/10.1109/ROBOT.2005.1570091
  8. Z. Chen and S. T. Birchfield, "Qualitative vision based path following," IEEE International Conference on Robotics and Automation, pp. 2686-2692, 2006.
  9. Z. Chen and S. T. Birchfield, "Qualitiative vision-based path following," IEEE Transactions on Robotics, vol. 25, no. 3, pp. 749-754, 2009. https://doi.org/10.1109/TRO.2009.2017140
  10. A. Diosi, A. Remazeilles, S. Segvic, and F. Chaumette, "Outdoor visual path following experiments," IEEE/RSJ International Conference on Robots and Systems, pp. 4265-4270, 2007. https://doi.org/10.1109/IROS.2007.4399247
  11. E. Royer, M. Lhuillier, M. Dhome, and J.-M. Lavest, "Monocular vision for mobile robot localization and autonomous navigation," International Journal of Computer Vision, vol. 74, no. 3, pp. 237-260, 2007. https://doi.org/10.1007/s11263-006-0023-y
  12. S. Birchfield, "KLT: An implementation of the Kanade Lucas- Tomasi feature tracker," [Online]. Available: http://www.ces.clemson.edu/-stb/klt/
  13. D. Nister. "An efficient solution to the five-point relative pose problem," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 26, no. 6, pp. 756-770, 2004. https://doi.org/10.1109/TPAMI.2004.17
  14. M. Fischler and R. Bolles, "Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography," Readings in computer vision: issues, problems, principles, and paradigms, pp. 726-740, 1987.
  15. I. S. Choi and J. E. Ha, "Performance comparison of visual path following using 2D and 3D information," Proc. of 2011 26th ICROS Annual Conference (in Korean), Gwangju, Korea, pp. 275-280, 2011.