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JRM Vol.19 No.3 pp. 290-297
doi: 10.20965/jrm.2007.p0290
(2007)

Paper:

Development of Obstacle Recognition System of Humanoids Using Relative Disparity Maps from Small Range Image Sensors

Naotaka Hikosaka, Kei Watanabe, and Kazunori Umeda

Department of Precision Mechanics, Chuo University, 1-13-27 Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan

Received:
October 23, 2006
Accepted:
March 24, 2007
Published:
June 20, 2007
Keywords:
small range image sensor, humanoid, relative disparity map, obstacle avoidance
Abstract
We discuss the recognition of obstacles by detecting a plane using relative disparity maps obtained from a small range image sensor incorporated in a humanoid. Our proposal enables easy plane detection and obstacle recognition using relative disparity from a reference plane alone. We built an integrated controller that feeds back obstacle information to the humanoid. We confirmed through experiments that the humanoid recognized obstacles and autonomously stopped walking.
Cite this article as:
N. Hikosaka, K. Watanabe, and K. Umeda, “Development of Obstacle Recognition System of Humanoids Using Relative Disparity Maps from Small Range Image Sensors,” J. Robot. Mechatron., Vol.19 No.3, pp. 290-297, 2007.
Data files:
References
  1. [1] K. Okada, S. Kagami, M. Inaba, and H. Inoue, “Plane Segment Finder: Algorithm, Implementation and Applications,” Proc. of International Conference on Robotics and Automation (ICRA’01), pp. 2120-2125, 2001.
  2. [2] N. Pears and B. Liang, “Ground Plane Segmentation for Mobile Robot Visual Navigation,” Proc. 2000 IEEE/RSJ International Conference on Intelligent Robots and System (IROS 2001), pp. 1513-1518, 2001.
  3. [3] For example, Point Grey Research Inc.
    http://www.ptgrey.com
  4. [4] T. Kanade, “Development of a Video-Rate Stereo Machine,” Proceedings of the 1994 ARPA Image Understanding Workshop (IUW’94), pp. 549-558, Nov., 1994.
  5. [5] R. Ozawa, Y. Takaoka, Y. Kida, K. Nishiwaki, J. Chestnutt, J. Kuffner, J. Kagami, H. Mizoguch, and H. Inoue, “Using Visual Odometry to Create 3D Maps for Online Footstep Planning,” Proceedings of IEEE International Conference on Systems, Man and Cybernetics (SMC2005), Hawaii, USA, pp. 2643-2648, Oct., 2005.
  6. [6] J. A. Beraldin, F. Blais, M. Rioux, J. Domery, and L. Cournoyer, “A video rate laser range camera for electronic boards inspection,” Proc. Vision’90 Conference, pp. 4-1-4-11, 1990.
  7. [7] T. Kanade, A. Gruss, and L. R. Carley, “A VLSI sensor based range finding system,” Robotics Research Fifth International Symposium, pp. 49-56, 1990.
  8. [8] K. Nakazawa and C. Suzuki, “Development of 3-D robot vision sensor with fiver grating: Fusion of 2-D intensity image and discrete range image,” Proc. 1991 International Conference on Industrial Electronics, Control and Instrumentation (IECON’91), pp. 2368-2372, 1991.
  9. [9] T. Tsubouchi, S. Takaki, Y. Kawaguchi, and S. Yuta, “A straight pipe observation from the inside by laser spot array and a TV camera,” Proc. 2000 IEEE/RSJ International Conference on Intelligent Robots and System (IROS 2000), pp. 82-87, 2000.
  10. [10] Y. Miyazaki, A. Ohya, and S. Yuta, “Obstacle Avoidance Behavior of Autonomous Mobile Robot using Fiber Grating Vision Sensor,” Proc. 2000 IEEE International, pp. 1925-1930, 2000.
  11. [11] M. Tateishi and K. Umeda, “Construction of a versatile compact range image sensor,” Proc. 7th Int. Conf. on Quality Control by Artificial Vision (QCAV2005), pp. 265-270, May 2005.
  12. [12] K. Umeda, “A Compact Range Image Sensor Suitable for Robots,” Proc. 2004 Int. Conf. On Robotics and Automation, pp. 3167-3172, April 2004.
  13. [13] http://www.stockeryale.com/

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