single-rb.php

JRM Vol.21 No.6 pp. 709-719
doi: 10.20965/jrm.2009.p0709
(2009)

Paper:

Hand-Eye Motion-Invariant Pose Estimation with Online 1-Step GA -3D Pose Tracking Accuracy Evaluation in Dynamic Hand-Eye Oscillation-

Mamoru Minami and Wei Song

Department of Human and Artificial Intelligence Systems, University of Fukui 3-9-1 Bunkyo, Fukui 910-0017, Japan

Received:
April 27, 2009
Accepted:
October 8, 2009
Published:
December 20, 2009
Keywords:
3-D pose measurement, motion feed-forward, unit quaternion
Abstract
This paper presents online pose measurement for a 3-dimensional (3-D) object detected by stereo hand-eye cameras. Our proposal improves 3-D pose tracking accuracy by compensating for the fictional motion of the target in camera images stemming from the ego motion of the hand-eye camera caused by dynamic manipulator oscillation. This motion feed-forward (MFF) is combined into the evolutionary search of a genetic algorithm (GA) and fitness evaluation based on stereo model matching whose pose is expressed using a unit quaternion. The proposal’s effectiveness was confirmed in simulation tracking an object’s 3-D pose adversely affected by hand-eye camera oscillations induced by dynamic effects of robot motion.
Cite this article as:
M. Minami and W. Song, “Hand-Eye Motion-Invariant Pose Estimation with Online 1-Step GA -3D Pose Tracking Accuracy Evaluation in Dynamic Hand-Eye Oscillation-,” J. Robot. Mechatron., Vol.21 No.6, pp. 709-719, 2009.
Data files:
References
  1. [1] K. Hashimoto and H. Kimura, “Visual Servoing - Nonlinear Observer Approach,” J. of the Robotics Society of Japan, Vol.13, No.7, pp. 986-993, 1995 (in Japanese).
  2. [2] A. De Luca, G. Oriolo, and P. R. Giordano, “On-line Estimation of Feature Depth for Image-Based Visual Servoing Schemes,” IEEE Int. Conf. on Robotics and Automation (ICRA2007).
  3. [3] Y. Nakabo and M. Ishikawa, “Visual Servoing using 1 ms High-Speed Vision,” J. of the Society of Instrument and Control Engineers, Vol.40, No.9, pp. 636-640, 2001 (in Japanese).
  4. [4] M. Minami, H. Suzuki, J. Agbanhan, and T. Asakura, “Visual Servoing to Fish and Catching Using Global/Local GA Search,” 2001 IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, Proc., pp. 183-188, 2001.
  5. [5] H. Suzuki and M. Minami, “Visual Servoing to catch fish Using Global/local GA Search,” IEEE/ASME Trans. on Mechatronics, Vol.10, Issue 3, pp. 352-357, 2005.
  6. [6] S. Benhimane and E. Mails, “Real-time image-based tracking of planes using efficient second-order minimization,” in Proc. of IEEE/RSJ Conf. on Intelligent Robot and Systems, pp. 1090-1097, Sep 28-Oct 2, 2004.
  7. [7] Y. Keller and A. Averbuch, “Fast motion estimation using bidirectional gradient methods,” IEEE Trans. on Image Processing, Vol.13, No.8, pp. 1042-1054, 2004.
  8. [8] J. T.-Y. Wen and K. Kreutz-Delgado, “The attitude control problem,” IEEE Trans. on Robotics and Automation, Vol.39, pp. 1148-1163, 1991.
  9. [9] S. Caccavale, C. Natale, B. Siciliano, and L. Villani, “Six-DOF Impedance Control BAsed on Angle/Axis Representations,” IEEE Trans. on Robotics and Automation, Vol.15, No.2, April 1999.
  10. [10] B. Xian, M. S. de Queiroz, D. Dawson, and I. Walker, “Task-Space Tracking Control of Robot Manipulators via Quaternion Feedback,” IEEE Trans. on Robotics and Automation, Vol.20, No.1, February 2004.
  11. [11] S. Arimoto, “Control Theory of Non-linear Mechanical System,” ISBN 0-19-856291-8.
  12. [12] M. W. Walker and D. E. Orin, “Efficient Dynamic Computer Simulation of Robotic Mechanisms,” ASME J. of DSMC, No.104, pp. 205-211.
  13. [13] W. Song, M. Minami, Y. Mae, and S. Aoyagi, “On-line Evolutionary Head Pose Measurement by Feedforward Stereo Model Matching,” IEEE Int. Conf. on Robotics and Automation (ICRA), pp. 4394-4400, 2007.
  14. [14] V. Lippiello, B. Siciliano, and L. Villani, “Position-Based Visual Servoing in Industrial Multirobot Cells Using a Hybrid Camara Configuration,” IEEE Trans. on Robotics, Vol.23, No.1, pp. 73-86, 2007.
  15. [15] T. Yoshida and M. Minami, “Prediction Servoing to Catch Escaping Fish Using Neural Network,” Proc. of the 2008 IEEE/ASME Int. Conf. on Advanced Intelligent Mechatronics, pp. 1225-1231.
  16. [16] M. Minami, J. Zhu, and M. Miura, “Real-time Evolutionary Recognition of Human with Adaptation to Environmental Condition,” The Second Int. Conf. on Computational Intelligence, Robotics and Autonomous Systems (CIRAS 2003).

*This site is desgined based on HTML5 and CSS3 for modern browsers, e.g. Chrome, Firefox, Safari, Edge, Opera.

Last updated on Oct. 01, 2024