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Adaptive motion selection for online hand–eye calibration

Published online by Cambridge University Press:  01 September 2007

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

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.

Type
Article
Copyright
Copyright © Cambridge University Press 2007

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