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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: [email protected], [email protected]
Yuncai Liu
Affiliation:
School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, P.R. China. E-mails: [email protected], [email protected]
*
*Corresponding author. E-mail: [email protected]
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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

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