The Position/Orientation Determination of a Mobile-Task Robot Using an Active Calibration Scheme

  • Jin, Tae-Seok (Department of Electronics Engineering, Pusan National University) ;
  • Lee, Jang-Myung (Department of Electronics Engineering, Pusan National University)
  • Published : 2003.10.01

Abstract

A new method of estimating the pose of a mobile-task robot is developed based upon an active calibration scheme. The utility of a mobile-task robot is widely recognized, which is formed by the serial connection of a mobile robot and a task robot. To be an efficient and precise mobile-task robot, the control uncertainties in the mobile robot should be resolved. Unless the mobile robot provides an accurate and stable base, the task robot cannot perform various tasks. For the control of the mobile robot, an absolute position sensor is necessary. However, on account of rolling and slippage of wheels on the ground, there does not exist any reliable position sensor for the mobile robot. This paper proposes an active calibration scheme to estimate the pose of a mobile robot that carries a task robot on the top. The active calibration scheme is to estimate a pose of the mobile robot using the relative position/orientation to a known object whose location, size, and shape are known a priori. For this calibration, a camera is attached on the top of the task robot to capture the images of the objects. These images are used to estimate the pose of the camera itself with respect to the known objects. Through the homogeneous transformation, the absolute position/orientation of the camera is calculated and propagated to get the pose of a mobile robot. Two types of objects are used here as samples of work-pieces: a polygonal and a cylindrical object. With these two samples, the proposed active calibration scheme is verified experimentally.

Keywords

References

  1. Aloiminos, J., Weiss, I. and Bandyopadhyay, A., 1988, 'Active Vision,' Int. Journal of Computer Vision, Vol. 1, No. 4, pp. 333-356 https://doi.org/10.1007/BF00133571
  2. Davies, E. R., 1989, 'Finding Ellipses Using the Generalized Hough Transform,' Pattern Recognition Letters, Vol. 9, pp. 87-96 https://doi.org/10.1016/0167-8655(89)90041-X
  3. Du,F. and Michael Brady, 1993, 'Self-Calibration of the Intrinsic Parameters of Cameras for Active Vision Systems,' Proc. IEEE. Conf. on Computer Vision and Pattern Recognition, pp. 15-17 https://doi.org/10.1109/CVPR.1993.341087
  4. Han, M. Y. and Jang M. Lee, 1997, 'Precision Control of a Mobile/Task Robot Using Visual Information,' Journal of The Korea Institute of Telematics and Electronics, in Korea, Vol. 34, No. 10, pp. 1089-1097
  5. Hanqi Zhuang and Zvi S. Roth, 1996, Camera-Aided Robot Calibration, CRC Press
  6. Heyden, A. and Astrom, K., 1997, 'Euclidean Reconstruction from Image Sequences with Varying and Unknown Focal Length and Principal Point,' Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, pp. 438-443 https://doi.org/10.1109/CVPR.1997.609362
  7. James L Crowley dnf Philippe Bobet, 1993, 'Dynamic Calibration of an Active Stereo Head, International Journal of Computer Vision, pp. 734-739 https://doi.org/10.1109/ICCV.1993.378141
  8. Jin-Gu Kang, Tae-Seok Jin, Min-Gyu Ki and Jang-Myung Lee, 2000, 'Optimal Configuration Control for a Mobile Manipulator,' KSME International Journal, Vol. 14, No. 6, pp. 605-621
  9. Jin-Hee Jang and Chang-Soo Han, 1997, 'The State Sensitivity Analysis of the Front Wheel Steering Vehicle : In the Time Domain,' KSME International Journal, Vol. 11, No. 6, pp. 595-604
  10. Johann Borenstein, 1995, 'Control and kinematic Design of Multi-Degree-of-Freedom Mobile Robots with Compliant Linkage,' IEEE Trans. on Robotics and Automation, Vol. 11, No. 1, pp. 21-35 https://doi.org/10.1109/70.345935
  11. Longuet-Higgins,H., C., 1981, 'A Computer Algorithm for Reconstructing a Scene from two Projections, in Nature Vol. 293, pp. 133-135 https://doi.org/10.1038/293133a0
  12. Luong, Q. T. and Faugeras, O. D., 1997, 'Self-Calibration of a Moving Camera from Point Correspondences and Fundamental Matrices,' International Journal of Computer Vision, Vol. 22, No. 3, pp. 261-289 https://doi.org/10.1023/A:1007982716991
  13. Pollefeys, M., Koch, R. and Gool, L. Van, 1998, 'Self-Calibration and Metric Reconstruction in Spite of Varying and Unknown Internal Camera Parameters, In International Conference on Computer Vision, pp. 90-95 https://doi.org/10.1109/ICCV.1998.710705
  14. Radu Horaud, Fadi Dornaika, Bart Lamiroy, Stephane Christyf, 1997, 'Object Pose : The Link between Weak Perspective, Paraperspective, and Full Perspective,' International Journal of Computer Vision, Vol. 22, No. 2, pp. 173-189 https://doi.org/10.1023/A:1007940112931
  15. Roger Pissard Gibollet and Patrick Rives, 1995, 'Applying Visual Servoing Techniques to Control a Mobile Hand-Eye System,' Proc. IEEE Int. Conf. on Robotics and Automation, Nagoya, Japan, pp. 166-171 https://doi.org/10.1109/ROBOT.1995.525280
  16. Safaee-Rad, R. Rchoukanov, I. Benhabib, B. and Smith, K. C., 1991, 'Accurate Parameter Estimation of Quadratic Curves from Grey-Level Images,' Comput. Vis. Graph. Image Process.:Image Understanding, Vol. 54, No. 2, pp. 259-274 https://doi.org/10.1016/1049-9660(91)90067-Y
  17. Stephen J. Maybank and Olivier D. Faugeras, 1992, 'A theory of Self-Calibration of a Moving Camera,' International Journal of Computer Vision, vol. 8, No. 2, pp. 123-151 https://doi.org/10.1007/BF00127171
  18. Sturm, P. and Maybank, S., 1999, 'On Plane-Based Camera Calibration : A General Algorithm, Singularities, Applications, Proc. IEEE Int. Conf. on Computer Vision and Pattern Recognition, Fort Collins, USA, pp. 432-437 https://doi.org/10.1109/CVPR.1999.786974
  19. Tsai, R. Y., 1987, 'A Versatile Camera Calibration Technique for High Accuracy 3-D Machine Vision Metrology Using o_-the-Shelf TV Cameras Lenses,' IEEE Trans. on Robotics and Automation, Vol. 3, pp. 323-344
  20. Yi Ma, Jana Kosecka and Shankar Sastry, 1999, 'Optimization Criteria and Geometric Algo rithms for Motion and Structure Estimation,' UC Berkeley Memorandom, No UCB/ERL M99/33, p. 35
  21. Yuncai Lui, Thomas S. Huang and Olivier D. Faugeras, 1990, 'Determination of Camera Location From 2-D to 3-D Line and Point Correspondences,' IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 13, No. 1, pp. 28-37 https://doi.org/10.1109/34.41381
  22. Zhengyou Zhang, 1997, 'Parameter Estimation Techniques: A Tutorial with Application to Conic Fitting,' Image and Vision Computing, Vol. 15, No. 1, pp. 57-76 https://doi.org/10.1016/S0262-8856(96)01112-2
  23. Zhuang, H., Roth, Z. S. and Wang, K., 1991, 'Robot Calibration by Mobile Camera System,' Proc. ASME Winter Ann. Mtg. Invited Session on Image Process Appl. Process Automation, DSC-Vol. 30, pp. 62-65