The da Vinci surgical robot is the most widely-used surgical robotics platform in the world thus far. Its intrinsic cable-driven properties lead to an end-effector positioning error in the order of millimeters [1], which can hinder its deployment in a shared control setup. To address this problem, we propose a calibration frame- work, which we test on the first generation da Vinci Research Kit (dVRK) [2]. Our statistical analysis shows that, after calibration, positioning accuracy has been improved. In addition, our method demonstrates bet- ter performance than model-based calibration methods when the training data set available is small.
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Cui et al. (2024) studied this question.
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