ConstraintSet::ConstraintSet():
m_nc(0),
m_internalPose(F_identity), m_externalPose(F_identity),
m_constraintCallback(NULL), m_constraintParam(NULL),
m_toggle(false),m_substep(false),
m_threshold(0.0),m_maxIter(0)
{
m_maxDeltaChi = e_scalar(0.52);
}
ConstraintSet::ConstraintSet(unsigned int _nc,double accuracy,unsigned int maximum_iterations):
m_nc(_nc),
m_Cf(e_zero_matrix(m_nc,6)),
m_Wy(e_scalar_vector(m_nc,1.0)),
m_y(m_nc),m_ydot(e_zero_vector(m_nc)),m_chi(e_zero_vector(6)),
m_S(6),m_temp(6),m_tdelta(6),
m_Jf(e_identity_matrix(6,6)),
m_U(e_identity_matrix(6,6)),m_V(e_identity_matrix(6,6)),m_B(e_zero_matrix(6,6)),
m_Jf_inv(e_zero_matrix(6,6)),
m_internalPose(F_identity), m_externalPose(F_identity),
m_constraintCallback(NULL), m_constraintParam(NULL),
m_toggle(false),m_substep(false),
m_threshold(accuracy),m_maxIter(maximum_iterations)
{
m_maxDeltaChi = e_scalar(0.52);
}
ControlledObject::ControlledObject():
Object(Controlled),m_nq(0),m_nc(0),m_nee(0)
{
// max joint variable = 0.52 radian or 0.52 meter in one timestep
m_maxDeltaQ = e_scalar(0.52);
}
bool WSDLSSolver::solve(const e_matrix& A, const e_vector& Wy, const e_vector& ydot, const e_matrix& Wq, e_vector& qdot, e_scalar& nlcoef)
{
unsigned int i, j, l;
e_scalar N, M;
// Create the Weighted jacobian
m_AWq = (A*Wq).lazy();
for (i=0; i<m_nc; i++)
m_WyAWq.row(i) = Wy(i)*m_AWq.row(i);
// Compute the SVD of the weighted jacobian
int ret;
if (m_transpose) {
m_WyAWqt = m_WyAWq.transpose();
ret = KDL::svd_eigen_HH(m_WyAWqt,m_V,m_S,m_U,m_temp);
} else {
ret = KDL::svd_eigen_HH(m_WyAWq,m_U,m_S,m_V,m_temp);
}
if(ret<0)
return false;
m_Wy_ydot = Wy.cwise() * ydot;
m_WqV = (Wq*m_V).lazy();
qdot.setZero();
e_scalar maxDeltaS = e_scalar(0.0);
e_scalar prevS = e_scalar(0.0);
e_scalar maxS = e_scalar(1.0);
for(i=0;i<m_ns;++i) {
e_scalar norm, mag, alpha, _qmax, Sinv, vmax, damp;
e_scalar S = m_S(i);
bool prev;
if (S < KDL::epsilon)
break;
Sinv = e_scalar(1.)/S;
if (i > 0) {
if ((prevS-S) > maxDeltaS) {
maxDeltaS = (prevS-S);
maxS = prevS;
}
}
N = M = e_scalar(0.);
for (l=0, prev=m_ytask[0], norm=e_scalar(0.); l<m_nc; l++) {
if (prev == m_ytask[l]) {
norm += m_U(l,i)*m_U(l,i);
} else {
N += std::sqrt(norm);
norm = m_U(l,i)*m_U(l,i);
}
prev = m_ytask[l];
}
N += std::sqrt(norm);
for (j=0; j<m_nq; j++) {
for (l=0, prev=m_ytask[0], norm=e_scalar(0.), mag=e_scalar(0.); l<m_nc; l++) {
if (prev == m_ytask[l]) {
norm += m_WyAWq(l,j)*m_WyAWq(l,j);
} else {
mag += std::sqrt(norm);
norm = m_WyAWq(l,j)*m_WyAWq(l,j);
}
prev = m_ytask[l];
}
mag += std::sqrt(norm);
M += fabs(m_V(j,i))*mag;
}
M *= Sinv;
alpha = m_U.col(i).dot(m_Wy_ydot);
_qmax = (N < M) ? m_qmax*N/M : m_qmax;
vmax = m_WqV.col(i).cwise().abs().maxCoeff();
norm = fabs(Sinv*alpha*vmax);
if (norm > _qmax) {
damp = Sinv*alpha*_qmax/norm;
} else {
damp = Sinv*alpha;
}
qdot += m_WqV.col(i)*damp;
prevS = S;
}
if (maxDeltaS == e_scalar(0.0))
nlcoef = e_scalar(KDL::epsilon);
else
nlcoef = (maxS-maxDeltaS)/maxS;
return true;
}