Hostname: page-component-8448b6f56d-42gr6 Total loading time: 0 Render date: 2024-04-24T00:58:36.526Z Has data issue: false hasContentIssue false
  • English
  • Français

Adaptive motion selection for online hand–eye calibration

Published online by Cambridge University Press:  01 September 2007

Jing Zhang ,
Fanhuai Shi  and
Yuncai Liu
Jing Zhang*
Affiliation:
Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, Shanghai, 200240, P.R. China.
Fanhuai Shi
Affiliation:
School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R. China. E-mails: fhshi@sjtu.edu.cn, whomliu@sjtu.edu.cn
Yuncai Liu
Affiliation:
School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R. China. E-mails: fhshi@sjtu.edu.cn, whomliu@sjtu.edu.cn
*
*Corresponding author. E-mail: zhjseraph@sjtu.edu.cn
Get access Rights & Permissions [Opens in a new window]

Summary

While a robot moves, online hand–eye calibration to determine the relative pose between the robot gripper/end-effector and the sensors mounted on it is very important in a vision-guided robot system. During online hand–eye calibration, it is impossible to perform motion planning to avoid degenerate motions and small rotations, which may lead to unreliable calibration results. This paper proposes an adaptive motion selection algorithm for online hand–eye calibration, featured by dynamic threshold determination for motion selection and getting reliable hand–eye calibration results. Simulation and real experiments demonstrate the effectiveness of our method.

Keywords

AdaptiveMotion selectionOnline hand-eye calibrationPolynomial regression
Type
Article
Information
Robotica , Volume 25 , Issue 5 , September 2007 , pp. 529 - 536
Copyright
Copyright © Cambridge University Press 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

1.Shiu, Y. C. and Ahmad, S., “Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form AX = XB,” IEEE Trans. Robot. Autom. 5, 16–29 (1989).CrossRefGoogle Scholar
2.Tsai, R. Y. and Lenz, R. K., “A new technique for fully autonomous and efficient 3d robotics hand/eye calibration,” IEEE Trans. Robot. Autom. 5, 345–358 (1989).CrossRefGoogle Scholar
3.Chen, H. “A screw motion approach to uniqueness analysis of head-eye geometry“. Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition, Maui, Hawaii (Jun. 1991). Pp. 145–151.Google Scholar
4.Wang, C., “Extrinsic calibration of a robot sensor mounted on a robot,” IEEE Trans. Robot. Autom. 8 (2), 161–175 (Apr. 1992).Google Scholar
5.Zhuang, H. Q. and Shiu, Y. C., “A noise-tolerant algorithm for robotic hand–eye calibration with or without sensor orientation measurement,” IEEE Trans. Syst., Man Cybern. 23 (4), 1168–1175 (1993).CrossRefGoogle Scholar
6.Horaud, R. and Dornaika, F., “Hand–eye calibration,” Int. J. Robot. Res. 14 (3), 195–210 (1995).CrossRefGoogle Scholar
7.Daniilidis, K., “Hand–eye calibration using dual quaternions,” Int. J. Robot. Res. 18 (3), 286–298 (1999).CrossRefGoogle Scholar
8.Motai, Y. and Kosaka, A., “SmartView: Hand–eye robotic calibration for active viewpoint generation and object grasping,” Proceedings of the IEEE International Conference on Robotics and Automation, Seoul, Korea, 2183–2190 (2001).Google Scholar
9.Muis, A. and Kouhei, O., “An iterative approach in pose measurement through hand–eye calibration,” Proceedings of the IEEE International Conference on Control Application, Istanbul, Turkey. (2003), pp. 983–988.Google Scholar
10.Malm, H. and Heyden, A., “Simplified intrinsic camera calibration and hand–eye calibration for robot vision,” Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, Las Vegas, Nevada (2003), pp. 1037–1043.Google Scholar
11.Angeles, J., Soucy, G. and Ferrie, F. P., “The online solution of the hand–eye problem,” IEEE Trans. Robot. Autom. 16, 720–731 (Dec. 2000).CrossRefGoogle Scholar
12.Andreff, N., Horaud, R. and Espiau, B., “On-line hand–eye calibration,” Proceedings of the International Conference on 3-D Digital Imaging and Modeling, 430 – 436 (Oct. 1999).Google Scholar
13.Andreff, N., Horaud, R. and Espiau, B., “Robot hand–eye calibration using structure-from-motion,” Int. J. Robot. Res. 20 (3), 228–248 (2001).CrossRefGoogle Scholar
14.Shi, F. H., Wang, J. H. and Liu, Y. C., “An Approach to improve online hand–eye calibration,” Proc. IbPRIA 2005, LNCS 3522, 647–655 (2005).Google Scholar
15.Zhuang, H. Q. and Melchinger, A., “Calibration of a Hand/eye matrix and a connection matrix using relative pose measurements,” Proceedings of the IEEE International Conference on Robotics and Automation, Albuquerque, New Mexico (1997), pp. 2888–2893.Google Scholar
16.Heikkila, T. and Matsushita, T., “Flexible hand–eye calibration for multi-camera systems,” IEEE/RSJ Int.Conf. Intell. Robots Syst. 2292–2297 (2000).Google Scholar
17.Hirsh, R. L. and De, G. N. Souza, “An interative approach to the hand–eye and base-borld calibratino problem,” Proceedings of the IEEE International Conference on Robotics and Automation. Seoul, Korea (2001), pp. 2171–2176.Google Scholar
18.Numeral, S tatistic group, Regression Analysis, (Chinese Academy of Science, Science Press, Beijing, China, 1974).Google Scholar
19.Ma, S. and Zhang, Z., Computer Vision, 2nd ed. (Beijing, China: Science Press, 1998. ch. 6).Google Scholar
20.Shi, F. H., Zhang, J., Liu, Y. C. and Zhao, Z. J.. “A hand–eye robotic model for total knee replacement surgery,” Proceedings of the 8th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI'2005) (2005), pp. 122–130.Google Scholar
21.Fassi, I. and Legnani, G., “Hand to sensor calibration: a geometrical interpretation of the matrix equation AX = XB”, J. Robot. Syst., 22 (9), 497–506 (2005).Google Scholar
22.Boctor, E., Iordachita, I., Fichtinger, G. and Hager, G. D., “Real-time quality control of tracked ultrasound,” Proceedings of the MICCAI Conference (2005), pp. 621–630.Google Scholar