Table 4 Comparative study of algorithms.
From: Accurate robot calibration via cascaded adaptive momentum LM and B-spline interpolated PSO
Models | Description |
|---|---|
M1 | The EKF algorithm, as described in7, is capable of handling non-Gaussian noise in the calibration system |
M2 | The LM algorithm introduced in5,6 is utilized for identifying deviations in kinematic parameters |
M3 | The PSO algorithm13, inspired by the foraging patterns of birds, is employed to obtain an optimal solution |
M4 | An efficient robot calibration method based on unscented Kalman filter and variable step-size Levenberg–Marquardt algorithm (UKF-VSLM)6 |
M5 | A Robot Calibration Method Based on Extended Kalman Filter and Improved Covariance Matrix Adaptive Evolution Strategy (EKF-ICMA-ES)21 |
M6 | A calibration method for industrial robot based on Levenberg–Marquardt and beetle antennae search algorithm (LM-BASA)22 |
M7 | The proposed AMLM method enhances the LM algorithm by utilizing momentum-based corrections, integrating historical updates |
M8 | The BIPSO method uses B-spline interpolation to enhance search efficiency by reducing reliance on discrete positions |
M9 | The proposed AMLM-BIPSO algorithm enhances robot calibration, significantly boosting its accuracy |
