Kinematics calibration is an important way to improve the accuracy of Parallel Manipulators (PMs). The robustness of kinematics calibration to measurement sensor noise can be improved by choosing measurement poses based on maximizing the observability index related to the identification Jacobian. The identification Jacobian matrix is a function of position and orientation of the PM, but the magnitudes of identification Jacobian matrix elements corresponding to position and orientation are different. This leads to a difference in the robustness of position and orientation to measurement sensor noise. Therefore, the identification Jacobian matrix was first normalized and the measurement poses were then selected through the observability index related to the normalized identification Jacobian to ensure the same robustness of position and orientation to measurement sensor noise. Through numerical examples, the precision of the structural parameters calibrated by using this method under three kinds of measurement noise is greatly improved compared with that of the traditional method, increasing from 1.007 5 mm to 0.336 7 mm, 0.100 9 mm to 0.033 7 mm, and 0010 1 nn to 0.003 4 mm, respectively. Compared with the traditional method, the calibration precision of position using this method basically remained unchanged, but the attitude accuracy was sharply higher, increasing from 0.015 2° to 0.003 3°, 0.003 3° to 0.000 3°, and 1.5×10-4° to 3.3×10-5°, respectively. The measured pose selected in this method was used to calibrate the Stewart parallel mechanism, and the mean error values of the position and attitude before and after calibration were reduced from 2.321 mm to 0.242 mm and from 0.246° to 0.025°, respectively, effectively improving the pose accuracy.