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• W1986247620 abstract "This paper addresses robust estimation of the uncalibrated visual-motor Jacobian for an image-based visual servoing (IBVS) system. The proposed method does not require knowledge of model or system parameters and is robust to outliers caused by various visual tracking errors, such as occlusion or mis-tracking. Previous uncalibrated methods are not robust to outliers and assume that the visual-motor data belong to the underlying model. In unstructured environments, this assumption may not hold. Outliers to the visual-motor model may deteriorate the Jacobian, which can make the system unstable or drive the arm in the wrong direction. We propose to apply a statistically robust M-estimator to reject the outliers. We compare the quality of the robust Jacobian estimation with the least squares-based estimation. The effect of outliers on the estimation quality is studied through MATLAB simulations and eye-in-hand visual servoing experiments using a WAM arm. Experimental results show that the Jacobian estimated by robust M-estimation is robust when up to 40% of the visual-motor data are outliers." @default.
• W1986247620 created "2016-06-24" @default.
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• W1986247620 date "2010-05-01" @default.
• W1986247620 modified "2023-10-10" @default.
• W1986247620 title "Robust Jacobian estimation for uncalibrated visual servoing" @default.
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• W1986247620 doi "https://doi.org/10.1109/robot.2010.5509911" @default.
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