The accuracy problem is one of the most concerning problems for the industrial application of a Stewart platform, and kinematic calibration is a feasible way to solve it. Although various calibration methods have been proposed, there is still room for improvement in the accuracy and robustness of these studies. In this article, a dimensionless error model is investigated, and the kinematic parame-ter errors are identified via the least-square method. Moreover, a novel method for measurement configurations selected based on the joint space is proposed. The simulation results show that the identification accuracy of the proposed method is better than that of the conventional method whose measurement configurations are uniformly selected in the workspace. A measurement method of the calibration experiment is suggested by the AICON 3D system - MoveInspect XR. The experimental results indicate that the position and orientation accuracy of the proposed method enhanced by 5% and 11% relative to the uniform selection method.

精度问题是Stewart平台工业应用中最为关注的问题之一，运动学标定是解决该问题的可行途径。尽管已经提出了各种校准方法，但这些研究的准确性和稳健性仍有改进的余地。在本文中，研究了无量纲误差模型，并通过最小二乘法识别运动参数误差。此外，提出了一种基于关节空间选择测量配置的新方法。仿真结果表明，所提方法的识别精度优于传统方法，其测量配置在工作空间内统一选择。AICON 3D系统-MoveInspect XR建议了校准实验的测量方法。实验结果表明，相对于均匀选择法，所提方法的定位精度提高了5%和11%。