Position-Constrained Calibration Compensation for Hand-Eye Calibration in Industrial Robots

Area of Science:

• Robotics
• Computer Vision
• Manufacturing Engineering

Background:

• Accurate hand-eye calibration is crucial for laser vision systems in industrial robot welding.
• Existing methods may lack efficiency and precision for optimizing the hand-eye transformation matrix.

Purpose of the Study:

• To develop and validate a position-constrained calibration compensation algorithm.
• To improve the accuracy and efficiency of hand-eye calibration for laser profilers and industrial robots.

Main Methods:

• Scanning a standard sphere with a laser profiler to determine theoretical sphere center coordinates.
• Collecting positional data using the robot's welding gun tip to obtain calibrated sphere center coordinates.
• Minimizing the error between theoretical and calibrated sphere centers to optimize the hand-eye transformation matrix.

Main Results:

• The proposed algorithm effectively optimizes the hand-eye transformation matrix.
• Average distance error in hand-eye calibration reduced from 4.5731 mm to 0.7069 mm post-compensation.
• Demonstrated significant improvement in calibration accuracy and reliability.

Conclusions:

• The position-constrained calibration compensation algorithm offers a reliable and effective solution for hand-eye calibration.
• The method enhances the performance of laser vision systems in robotic welding applications.
• The optimized hand-eye transformation matrix leads to more precise robotic operations.