In the application of parallel mechanisms, it is necessary to calibrate the kinematic parameters and improve the positioning accuracy for accurate task performance. However, there are strong correlations between all the parameters in the kinematic calibration of a parallel mechanism. Therefore, it is difficult to identify all kinematic parameters included in a kinematic model of the parallel mechanism from measuring data. In this study, we proposed to use a priori knowledge of the kinematic

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... meters to eliminate their correlation and to give robustness to the calibration. A priori knowledge can be given without extra measurement when the manufacturing process of the mechanism is under quality control. Using a priori knowledge, all kinematic parameters of the parallel mechanism are identified in the artefact calibration without divergence. First, an artefact calibration with a priori knowledge is formulated. Second, the estimation of a priori knowledge under quality control is described. Finally, the robustness and effectiveness of the artefact calibration with a priori knowledge is demonstrated through simulations.