Precision Denavit-Hartenberg Parameter Calibration for Industrial Robots Using a Laser Tracker System and Intelligent...

Area of Science:

• Robotics
• Metrology
• Optimization Algorithms

Background:

• Industrial robot precision relies on accurate end-effector positioning via forward kinematics (FKs).
• FKs depend on Denavit-Hartenberg (DH) parameters, which are susceptible to uncertainties from wear, manufacturing, and calibration errors.
• Reducing DH parameter uncertainty is crucial for enhancing FK accuracy.

Purpose of the Study:

• To calibrate industrial robot DH parameters to improve FK accuracy.
• To evaluate the effectiveness of metaheuristic optimization algorithms for DH parameter calibration.
• To quantify the accuracy improvement achieved using laser tracker measurements.

Main Methods:

• Utilized differential evolution, particle swarm optimization, artificial bee colony, and gravitational search algorithms for DH parameter calibration.
• Employed a Leica AT960-MR laser tracker system for high-accuracy positional measurements (< 3 μm/m).
• Applied metaheuristic optimization to laser tracker data to refine DH parameter values.

Main Results:

• The artificial bee colony optimization algorithm demonstrated significant improvement in FK accuracy.
• Mean absolute errors for static and near-static motion decreased from 75.4 μm to 60.1 μm.
• Achieved a 20.3% improvement in industrial robot FK accuracy using the proposed calibration method.

Conclusions:

• Metaheuristic optimization, particularly the artificial bee colony algorithm, effectively calibrates industrial robot DH parameters.
• Accurate metrology, like laser tracking, is vital for precise robot calibration.
• The developed approach significantly enhances the accuracy of industrial robot forward kinematics.