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Efficiently Recording the Eye-Hand Coordination to Incoordination Spectrum
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Hand-Eye Calibration in Visually-Guided Robot Grinding.

Wen-Long Li, He Xie, Gang Zhang

    IEEE Transactions on Cybernetics
    |October 30, 2015
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a new, cost-effective method for robot hand-eye calibration in belt grinding, improving automation accuracy for blade manufacturing by accounting for joint and pose errors.

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    Area of Science:

    • Robotics
    • Manufacturing Automation
    • Computer Vision

    Background:

    • Visually-guided robot grinding is a key automation technique for blade manufacturing.
    • Accurate hand-eye calibration is crucial for robot grinding but often complex and expensive.
    • Existing methods may not fully address joint and pose parameter errors.

    Purpose of the Study:

    • To develop a novel, economical, and simple hand-eye calibration approach for robot belt grinding.
    • To enhance the accuracy of robot grinding by considering both joint and pose parameter errors.
    • To provide a closed-form solution for calculating calibration parameters.

    Main Methods:

    • A new hand-eye calibration equation incorporating joint and pose parameter errors was formulated.
    • An objective function was defined and solved to obtain compensated values.
    • A single criterion sphere was utilized for parameter calculation, avoiding complex tracking systems.

    Main Results:

    • The proposed method successfully calculated 30 compensated values (24 joint, 6 pose parameters) in a closed solution.
    • Experimental validation through calibration and blade grinding demonstrated the method's effectiveness.
    • The approach proved to be economical and simpler compared to laser tracker methods.

    Conclusions:

    • The developed hand-eye calibration method offers an efficient and accurate solution for robot belt grinding.
    • This technique enhances automation in blade manufacturing by improving the precision of visually-guided robots.
    • The proposed approach provides a practical and cost-effective alternative for industrial applications.