DOI QR코드

DOI QR Code

Obstacle Position Detection on an Inclined Plane Using Randomized Hough Transform and Corner Detection

랜덤하프변환과 코너추출을 이용한 경사면의 장애물 위치 탐색

  • Received : 2011.02.20
  • Accepted : 2011.03.29
  • Published : 2011.05.01

Abstract

This paper suggests a judgement method for an inclined plane before entrance of it and the detection of obstacle position. Main idea is started from the assumption that obstacle is always on the bottom plane, and corner appears at this position. The process to detect the obstacle consists of three steps. First the 3D data using stereo matching is acquired to detect an obstacle. Second a bottom plane is extracted by using limit condition. Last the obstacle position is found by using Harris corner detection. Obstacle position detection on an inclined plane was verified by outdoor and indoor experiment. In error analysis, it is confirmed that an average error of obstacle detection in outdoor was larger than the error in indoor but the error are within about 0.030 m. This method will be applied to unmanned vehicles to navigate under various environment.

Acknowledgement

Supported by : 정보통신산업진흥원

References

  1. V. Agarwal, S. Member, IEEE, N. V. Murali, and C. Chandramouli, "A cost-effective ultrasonic sensor-based driver-assistance system for congested traffic conditions," IEEE Transactions on Intelligent Transportation Systems, vol. 10, no. 3, pp. 486, Sep. 2009. https://doi.org/10.1109/TITS.2009.2026671
  2. K. R. Lee, S. K. Hong, and D. K. Jwa "Obstacle detection and classification algorithm using a laser scanner," The Transactions of Korean Institute of Electrical Engineers, vol. 57, no. 4, pp. 677-685, Apr. 2008.
  3. M. S. Darms, P. E. Rybski, C. Baker, and C. Urmson, "Obstacle detection and tracking for the urban challenge," IEEE Transactions on Intelligent Transportation Systems, vol. 10, no. 3, pp 475-485, Sep. 2009. https://doi.org/10.1109/TITS.2009.2018319
  4. M. Schwarzinger, T. Zielke, D. Noll, M. Brauchmann, and W. V. Seelen, "Vision-based car-following: detection, tracking,and identification," Proc. of the Intelligent Vehicles 92 Symposium, Detroit, USA, vol. 10 no. 9 pp. 24-29, Jun. 1992.
  5. R. Ponticelli P. Gonzalez de Santoz, "Obtaining terrain maps and obstacle contours for terrain-recognition tasks," Mechatronics, vol. 20, no. 2 pp. 236-250, 2010. https://doi.org/10.1016/j.mechatronics.2009.11.008
  6. D.-J. Kang, S.-J. Lim, J.-E. Ha, and M.-H. Jeong, "A detection cell using multiple points of a rotating triangle to find local planar regions from stereo depth data," Pattern Recognition Letters, vol. 30, no. 5, pp. 486-493, 2009. https://doi.org/10.1016/j.patrec.2008.11.011
  7. K. Okada, S. Kagami, M. Inaba, and H. Inoue, "Plane segment finder: Algorithm, implementation and applications," International Conference on Robotics & Automation, Seoul, Korea, vol. 2, no. 7, pp, 21-26, May 2001.
  8. K. H. Chen and W. H Tsai, "Vision-based obstacle detection and avoidance for autonomous land vehicle navigation in outdoor roads," Automation in Construction, vol. 10, no. 1, pp. 1-25, Oct. 2000. https://doi.org/10.1016/S0926-5805(99)00010-2
  9. D. S. Jang, "Recognition of 3D environment for intelligent robots," Korean Society for Internet Information, vol. 7, no. 5, pp. 135-145, Oct. 2006.
  10. H. D. Lee, D. Y. Yum, and H. Kang, "A study of the 3D-reconstruction of indoor using stereo camera system," International Journal of Fuzzy Logic and Intelligent Systems, vol. 15, no. 1, pp. 42-47, Jan. 2005. https://doi.org/10.5391/JKIIS.2005.15.1.042
  11. J. Y. Lee and K. Y. Lee, "Stereo-Vision based road slope estimation and free space detection on road," Journal of Institute of Control, Robotics and Systems(in Korean), vol. 17, no. 3, pp. 199-205, Mar. 2011. https://doi.org/10.5302/J.ICROS.2011.17.3.199
  12. N. Kiryati, Y. Eldar, and A. M. Bruckstein, "Probabilistic Hough transform," Pattern Recogn. Lett. 24, vol. 9. no. 1, pp. 303-316, 1991.
  13. V. F. Leavers, "The dynamic generalized Hough transform: its relationship to the probabilistic Hough transforms and an application to the concurrent detection of circles and ellipses," CVGIP: Image Understanding, vol. 56. no. 3, pp. 381-398, 1992. https://doi.org/10.1016/1049-9660(92)90049-9
  14. K. S. Lee and R. H. Jo, "The gradient analysis of the korean peninsula by using DEM," The Korean Association of Geographic Informaiton Studies, vol. 3, no. 1, pp. 35-43, Apr. 2000.
  15. C. Harris and M. Stephens, "A combined corner and edge detector," Proc. 4th Alvey Vis. Conf., Manchester, vol. 4, no. 1, pp. 189-192, Aug. 1988.