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Adaptive self-calibration of vision-based robot systems

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3 Author(s)
P. Liang ; Center for Robotic Syst. in Microelectron., California Univ., Santa Barbara, CA, USA ; Y. L. Chang ; S. Hackwood

An adaptive self-learning process to dynamically and continuously learn the transformation between the camera space and the robot space is discussed. The process is referred to as the adaptive self-calibration of hand-eye systems in which a visual-feedback-based self-learning process is used for dynamically and continuously learning the hand-eye transformation through repetitive operation trials. The hand-eye system calibration is used in situ and in real time while the system is operating. Recursive real-time implementation using adaptive and square-root Kalman filtering techniques is described and recent related research is reviewed. An experimental stereo-vision-based hand-eye system is described. Both simulation and experimental results are presented

Published in:

IEEE Transactions on Systems, Man, and Cybernetics  (Volume:19 ,  Issue: 4 )