3dpcp/.svn/pristine/aa/aab1465d67abf5a9f1931f8e19ebeefa1a6ddee0.svn-base

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2012-09-16 12:33:11 +00:00
/*
* icp6Dlumeuler implementation
*
* Copyright (C) Andreas Nuechter, Alexandru-Eugen Ichim
*
* Released under the GPL version 3.
*
*/
/** @file
* @brief Implementation of the ICP error function minimization via
* linearization using euler angles
*
* @author Andreas Nuechter. Jacobs University Bremen gGmbH, Germany
* @author Alexandru-Eugen Ichim. Jacobs University Bremen gGmbH, Germany
*
*/
#include "slam6d/icp6Dlumeuler.h"
#include "slam6d/globals.icc"
#include <iomanip>
using std::ios;
using std::resetiosflags;
using std::setiosflags;
#include "newmat/newmat.h"
#include "newmat/newmatap.h"
using namespace NEWMAT;
/**
* computes the rotation matrix consisting
* of a rotation and translation that
* minimizes the root-mean-square error of the
* point pairs using linearization with euler angles
* @param pairs Vector of point pairs (pairs of corresponding points)
* @param *alignfx The resulting transformation matrix
* @return Error estimation of the matching (rms)
*/
double icp6D_LUMEULER::Point_Point_Align(const vector<PtPair>& pairs, double *alignfx,
const double centroid_m[3], const double centroid_d[3])
{
// alignxf is filled with the current pose, rPos is the translation, rPosTheta are the 3 euler angles theta_x, theta_y, theta_z
double rPos[3], rPosTheta[3];
Matrix4ToEuler(alignfx, rPosTheta, rPos);
double error = 0;
double sum = 0.0;
for(unsigned int i = 0; i < pairs.size(); i++){
sum += sqr(pairs[i].p1.x - pairs[i].p2.x)
+ sqr(pairs[i].p1.y - pairs[i].p2.y)
+ sqr(pairs[i].p1.z - pairs[i].p2.z) ;
}
error = sqrt(sum / (double)pairs.size());
if (!quiet) {
cout.setf(ios::basefield);
cout << "LUMEULER RMS point-to-point error = "
<< resetiosflags(ios::adjustfield) << setiosflags(ios::internal)
<< resetiosflags(ios::floatfield) << setiosflags(ios::fixed)
<< std::setw(10) << std::setprecision(7)
<< error
<< " using " << std::setw(6) << (int)pairs.size() << " points" << endl;
}
/////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////
double x = 0.0, y = 0.0, z = 0.0, dx = 0.0, dy = 0.0, dz = 0.0, sx = 0.0, sy = 0.0, sz = 0.0, xpy = 0.0, xpz = 0.0, ypz = 0.0, xy = 0.0, yz = 0.0, xz = 0.0;
/// MZ = M^T * Z
ColumnVector MZ(6); MZ = 0.0;
/// MM = M^T * M
SymmetricMatrix MM(6); MM = 0.0;
for(unsigned int i = 0; i < pairs.size(); ++i) {
/// temporary values that we shall use multiple times in the subsequent computations
x = (pairs[i].p1.x + pairs[i].p2.x) / 2.0;
y = (pairs[i].p1.y + pairs[i].p2.y) / 2.0;
z = (pairs[i].p1.z + pairs[i].p2.z) / 2.0;
dx = pairs[i].p1.x - pairs[i].p2.x;
dy = pairs[i].p1.y - pairs[i].p2.y;
dz = pairs[i].p1.z - pairs[i].p2.z;
/// sums of each coordinate
sx += x;
sy += y;
sz += z;
/// sums of squares of pairs of coordinates
xpy += x*x + y*y;
xpz += x*x + z*z;
ypz += y*y + z*z;
/// sums of products of pairs of coordinates
xy += x*y;
xz += x*z;
yz += y*z;
/// incrementally construct M^T * Z
MZ(1) += dx;
MZ(2) += dy;
MZ(3) += dz;
MZ(4) += -z*dy + y*dz;
MZ(5) += -y*dx + x*dy;
MZ(6) += z*dx - x*dz;
}
/// construct M^T * M
MM(1,1) = MM(2,2) = MM(3,3) = pairs.size();
MM(4,4) = ypz;
MM(5,5) = xpy;
MM(6,6) = xpz;
MM(1,5) = MM(5,1) = -sy;
MM(1,6) = MM(6,1) = sz;
MM(2,4) = MM(4,2) = -sz;
MM(2,5) = MM(5,2) = sx;
MM(3,4) = MM(4,3) = sy;
MM(3,6) = MM(6,3) = -sx;
MM(4,5) = MM(5,4) = -xz;
MM(4,6) = MM(6,4) = -xy;
MM(5,6) = MM(6,5) = -yz;
ColumnVector Ehat(6);
Ehat = MM.i() * MZ;
double cosx = cos(rPosTheta[0]), cosy = cos(rPosTheta[1]), cosz = cos(rPosTheta[2]);
double sinx = sin(rPosTheta[0]), siny = sin(rPosTheta[1]), sinz = sin(rPosTheta[2]);
double tx = rPos[0], ty = rPos[1], tz = rPos[2];
/// create transform matrix of the first scan
Matrix T1(4, 4); T1 = IdentityMatrix(4);
T1(1, 4) = tx;
T1(2, 4) = ty;
T1(3, 4) = tz;
T1(1, 1) = cosy*cosz;
T1(1, 2) = -cosy*sinz;
T1(1, 3) = siny;
T1(2, 1) = cosz*sinx*siny + cosx*sinz;
T1(2, 2) = cosx*cosz-sinx*siny*sinz;
T1(2, 3) = -cosy*sinx;
T1(3, 1) = sinx*sinz - cosx*cosz*siny;
T1(3, 2) = cosz*sinx + cosx*siny*sinz;
T1(3, 3) = cosx*cosy;
/// create matrix H
Matrix H(6, 6); H = IdentityMatrix(6);
H(1, 5) = -tz*cosx + ty*sinx;
H(1, 6) = ty*cosx*cosy + tz*cosy*sinx;
H(2, 4) = tz;
H(2, 5) = -tx*sinx;
H(2, 6) = -tx*cosx*cosy + tz*siny;
H(3, 4) = -ty;
H(3, 5) = tx*cosx;
H(3, 6) = -tx*cosy*sinx - ty*siny;
H(4, 6) = siny;
H(5, 5) = sinx;
H(5, 6) = cosx*cosy;
H(6, 5) = cosx;
H(6, 6) = -cosy*sinx;
/// the vector Xhat is the pose estimation of the second scan = the final pose of the first scan
ColumnVector Xhat(6); Xhat << rPos[0] << rPos[1] << rPos[2] << rPosTheta[0] << rPosTheta[1] << rPosTheta[2];
ColumnVector X = Xhat - H.i()*Ehat;
cosx = cos(X(4)), cosy = cos(X(5)), cosz = cos(X(6));
sinx = sin(X(4)), siny = sin(X(5)), sinz = sin(X(6));
/// transform of the second scan as computed so far
Matrix T2(4, 4); T2 = IdentityMatrix(4);
T2(1, 4) = X(1);
T2(2, 4) = X(2);
T2(3, 4) = X(3);
T2(1, 1) = cosy*cosz;
T2(1, 2) = -cosy*sinz;
T2(1, 3) = siny;
T2(2, 1) = cosz*sinx*siny + cosx*sinz;
T2(2, 2) = cosx*cosz-sinx*siny*sinz;
T2(2, 3) = -cosy*sinx;
T2(3, 1) = sinx*sinz - cosx*cosz*siny;
T2(3, 2) = cosz*sinx + cosx*siny*sinz;
T2(3, 3) = cosx*cosy;
/// the incremental transform calculated from the absolute poses of the two scans
Matrix T_inc = T1 * T2.i();
/// convert our 4x4 transform to column-wise opengl form
alignfx[0] = T_inc(1, 1);
alignfx[1] = T_inc(2, 1);
alignfx[2] = T_inc(3, 1);
alignfx[3] = 0.0;
alignfx[4] = T_inc(1, 2);
alignfx[5] = T_inc(2, 2);
alignfx[6] = T_inc(3, 2);
alignfx[7] = 0.0;
alignfx[8] = T_inc(1, 3);
alignfx[9] = T_inc(2, 3);
alignfx[10]= T_inc(3, 3);
alignfx[11]= 0.0;
alignfx[12]= T_inc(1, 4);
alignfx[13]= T_inc(2, 4);
alignfx[14]= T_inc(3, 4);
alignfx[15]= 1.0;
/////////////////////////////////////////////////////////
/////////////////////////////////////////////////////////
return error;
}