Visual Servoing Platform  version 3.2.0 under development (2018-12-10)
calibrate-hand-eye.cpp

Example of hand-eye calibration to estimate extrinsic camera parameters, ie hand-eye homogeneous transformation corresponding to the transformation between the robot end-effector and the camera.

/****************************************************************************
*
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* Copyright (C) 2005 - 2017 by Inria. All rights reserved.
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* Inria Rennes - Bretagne Atlantique
* Campus Universitaire de Beaulieu
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*
* Description:
* Hand-eye calibration example to estimate hand to eye transformation.
*
* Authors:
* Fabien Spindler
*
*****************************************************************************/
#include <iomanip>
#include <sstream>
#include <stdio.h>
#include <vector>
#include <visp3/core/vpDebug.h>
#include <visp3/core/vpExponentialMap.h>
#include <visp3/core/vpIoTools.h>
#include <visp3/io/vpParseArgv.h>
#include <visp3/vision/vpHandEyeCalibration.h>
int main()
{
try {
// We want to calibrate the hand-eye extrinsic camera parameters from 6
// couple of poses: cMo and wMe
const unsigned int N = 6;
// Input: six couple of poses used as input in the calibration proces
std::vector<vpHomogeneousMatrix> cMo(N); // eye (camera) to object
// transformation. The object
// frame is attached to the
// calibrartion grid
std::vector<vpHomogeneousMatrix> wMe(N); // world to hand (end-effector) transformation
// Output: Result of the calibration
vpHomogeneousMatrix eMc; // hand (end-effector) to eye (camera) transformation
// Initialize an eMc transformation used to produce the simulated input
// transformations cMo and wMe
vpTranslationVector etc(0.1, 0.2, 0.3);
erc[0] = vpMath::rad(10); // 10 deg
erc[1] = vpMath::rad(-10); // -10 deg
erc[2] = vpMath::rad(25); // 25 deg
eMc.buildFrom(etc, erc);
std::cout << "Simulated hand-eye transformation: eMc " << std::endl;
std::cout << eMc << std::endl;
std::cout << "Theta U rotation: " << vpMath::deg(erc[0]) << " " << vpMath::deg(erc[1]) << " " << vpMath::deg(erc[2])
<< std::endl;
vpColVector v_c(6); // camera velocity used to produce 6 simulated poses
for (unsigned int i = 0; i < N; i++) {
v_c = 0;
if (i == 0) {
// Initialize first poses
cMo[0].buildFrom(0, 0, 0.5, 0, 0, 0); // z=0.5 m
wMe[0].buildFrom(0, 0, 0, 0, 0, 0); // Id
} else if (i == 1)
v_c[3] = M_PI/8 ;
else if (i == 2)
v_c[4] = M_PI/8 ;
else if (i == 3)
v_c[5] = M_PI/10 ;
else if (i == 4)
v_c[0] = 0.5;
else if (i == 5)
v_c[1] = 0.8;
vpHomogeneousMatrix cMc; // camera displacement
cMc = vpExponentialMap::direct(v_c); // Compute the camera displacement
// due to the velocity applied to
// the camera
if (i > 0) {
// From the camera displacement cMc, compute the wMe and cMo matrices
cMo[i] = cMc.inverse() * cMo[i - 1];
wMe[i] = wMe[i - 1] * eMc * cMc * eMc.inverse();
}
}
// if (1) {
if (1) {
for (unsigned int i = 0; i < N; i++) {
wMo = wMe[i] * eMc * cMo[i];
std::cout << std::endl << "wMo[" << i << "] " << std::endl;
std::cout << wMo << std::endl;
std::cout << "cMo[" << i << "] " << std::endl;
std::cout << cMo[i] << std::endl;
std::cout << "wMe[" << i << "] " << std::endl;
std::cout << wMe[i] << std::endl;
}
}
// Reset the eMc matrix to eye
eMc.eye();
// Compute the eMc hand to eye transformation from six poses
// - cMo[6]: camera to object poses as six homogeneous transformations
// - wMe[6]: world to hand (end-effector) poses as six homogeneous
// transformations
std::cout << std::endl << "Output: hand-eye calibration result: eMc estimated " << std::endl;
std::cout << eMc << std::endl;
eMc.extract(erc);
std::cout << "Theta U rotation: " << vpMath::deg(erc[0]) << " " << vpMath::deg(erc[1]) << " " << vpMath::deg(erc[2])
<< std::endl;
return EXIT_SUCCESS;
} catch (const vpException &e) {
std::cout << "Catch an exception: " << e << std::endl;
return EXIT_FAILURE;
}
}