Probabilistic Framework for Hand-Eye and Robot-World Calibration AX = YB

MATLAB implementation of Probabilistic Framework for Hand-Eye and Robot-World Calibration AX = YB (IEEE T-RO 2023).

Paper Link: https://ieeexplore.ieee.org/abstract/document/9931998

Overview

This is a MATLAB code of probabilistic solver for hand-eye and robot-world calibration AX = YB, the detailed algorithm of which is presented in the paper entitled "Probabilistic Framework for Hand–Eye and Robot–World Calibration AX=YB" (IEEE T-RO 2023). The algorithm incorporates different individual noise distributions of measurements A_i and B_i, and also provides calibration uncertainty as an error covariance matrix.

• The code has been uploaded for the published version of the paper. (10/20/2023)
• An instruction file instruction.docx has been added. (10/20/2023)
• Codes from https://github.com/ihtishamaliktk/RWHE-Calib were used in experiments. Please allow us some time to clean up the codes and properly cite them.

Instruction

• Please read instruction.docx for more details.

1. See the three system noise configurations presented in the paper and select one that best fits your system.
2. Calibration functions are different between noise configurations 1,2 and noise configuration 3.
   • For noise configurations 1 and 2, call

      [X, Y] = solveAXYB_prob(A, B, X0, Y0, invSig_wN, invSig_pN, invSig_wM, invSig_pM, noiseConf, step_R, step_p)
     

   • For noise configuration 3, call

      [X, Y] = solveAXYB_prob_noiselessA(A, B, X0, Y0, invSig_wM, invSig_pM, step_R, step_p)
     

Here X, Y are the calibration results, and A, B are the measurements pairs in size of 4 X 4 X n each (n is the number of measurement pairs). invSig_wN, invSig_pN, invSig_wM, invSig_pM are the inverses of rotational and translational noise covariances of A and B, each of which is in size of 3 X 3 X n. step_R, step_p are stepsizes for rotation and translation, respectively.

Demos

• The script main_example1.m demonstrates a simple example of how to use the solver.
• The scripts main_fig5.m, main_fig6.mm, ... generate the figures in the paper.