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Updated: Aug 16, 2025

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Stereo vision-based Kinematic calibration method for the Stewart platforms.

Lei Fu, Ming Yang, Zhihua Liu

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    This study introduces a dimensionless error model and stereo vision method for Stewart platform kinematic calibration. The approach significantly enhances accuracy, reducing position and orientation errors for industrial applications.

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    Area of Science:

    • Robotics and Control Systems
    • Mechanical Engineering
    • Metrology

    Background:

    • Stewart platforms are crucial for industrial applications requiring high precision.
    • Kinematic calibration is essential for ensuring the accuracy and performance of Stewart platforms.
    • Existing methods for identifying geometric parameter errors have limitations in effectiveness and accuracy.

    Purpose of the Study:

    • To improve the effectiveness of the least squares algorithm for identifying geometric parameter errors in Stewart platforms.
    • To develop a novel dimensionless error model tailored to the structural characteristics of Stewart platforms.
    • To propose and validate a stereo vision-based measurement method for determining the 6-degree-of-freedom (DOF) pose of the moving platform.

    Main Methods:

    • Investigation of an applicable dimensionless error model based on Stewart platform structural characteristics.
    • Proposal of a novel stereo vision-based measurement technique for 6-DOF pose acquisition.
    • Simulation and experimental validation of the dimensionless error model and calibration method on a prototype.

    Main Results:

    • The dimensionless error model demonstrated efficiency in identification simulations.
    • Kinematic calibration experiments on a prototype yielded significant error reduction.
    • Position error decreased to 0.261 mm (89.720% improvement), and orientation error decreased to 0.051° (90.351% improvement).

    Conclusions:

    • The proposed dimensionless error model and stereo vision method effectively improve the kinematic calibration accuracy of Stewart platforms.
    • The enhanced accuracy significantly boosts the motion orbit performance for industrial applications.
    • This research provides a robust solution for achieving high-precision industrial robotic systems.