Marker-Based Pose Estimation of End Effectors in Industrial Robot Visual Servoing: Error Modeling and Placement...

Area of Science:

• Robotics
• Computer Vision
• Control Systems

Background:

• Accurate end-effector pose estimation is crucial for industrial robot visual servoing systems.
• Pose errors directly impact feedback quality and trajectory tracking performance.

Purpose of the Study:

• To develop a model for predicting end-effector pose estimation errors in visual servoing.
• To analyze marker placement factors influencing these errors.
• To provide guidelines for optimizing marker configuration.

Main Methods:

• Established a propagation model from marker measurement errors to end-effector pose errors.
• Derived covariance expressions for pose estimation errors.
• Analyzed marker-set spatial range, distribution balance, centroid offset, and marker number.

Main Results:

• Quantified the impact of marker placement on translational and rotational errors.
• Determined the influence of the number of markers on pose estimation accuracy.
• Validated the analytical model using Monte Carlo simulations and experimental data.

Conclusions:

• The developed model accurately predicts pose estimation errors.
• Guidelines for marker placement and number are provided to enhance visual servoing accuracy.
• Optimized marker configurations can significantly improve robot control performance.