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• W1561300068 abstract "Robot calibration is to improve the accuracy of the robot model so as to achieve better positioning accuracy within the robot work cell. Model based calibration approaches are in general limited to compensating for geometric errors and are unable to compensate for error sources that do not fit within the proposed robot model. In order to compensate for the unmodeled error sources, a Radial Basis Function (RBF) Neural Network (NN) augmented robot model is proposed together with a two stage calibration process for training the NN. A simulation and an experimental study are conducted to verify the effectiveness of the proposed solution." @default.
• W1561300068 created "2016-06-24" @default.
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• W1561300068 date "2015-05-01" @default.
• W1561300068 modified "2023-09-22" @default.
• W1561300068 title "Calibration of industrial robots with product-of-exponential (POE) model and adaptive Neural Networks" @default.
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• W1561300068 doi "https://doi.org/10.1109/icra.2015.7139380" @default.
• W1561300068 hasPublicationYear "2015" @default.
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