International Journal of Robotics Research
A New Approach to Hand-Eye Calibration
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 1
3DIM'99 Proceedings of the 2nd international conference on 3-D digital imaging and modeling
Data Selection for Hand-eye Calibration: A Vector Quantization Approach
International Journal of Robotics Research
An adaptive selection of motion for online hand-eye calibration
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
An overview of robot-sensor calibration methods for evaluation of perception systems
Proceedings of the Workshop on Performance Metrics for Intelligent Systems
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Online implementation of robotic hand-eye calibration consists in determining the relative pose between the robot gripper/end-effector and the sensors mounted on it, as the robot makes unplanned movement. With noisy measurements, inevitable in real applications, the calibration is sensitive to small rotations. Moreover, degenerate cases such as pure translations are of no effect in hand-eye calibration. This paper proposes an algorithm of motion selection for hand-eye calibration. Using this method, not only can we avoid the degenerate cases, but also the small rotations to decrease the calibration error. Thus, the procedure lends itself to an online implementation of hand-eye calibration, where degenerate cases and small rotations frequently occur in the sampled motions. Simulation and real experiments validate our method.