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- /** \file itasc/WSDLSSolver.cpp
- * \ingroup itasc
- */
- /*
- * WDLSSolver.hpp.cpp
- *
- * Created on: Jan 8, 2009
- * Author: rubensmits
- */
- #include "WSDLSSolver.hpp"
- #include "kdl/utilities/svd_eigen_HH.hpp"
- #include <cstdio>
- namespace iTaSC {
- WSDLSSolver::WSDLSSolver() :
- m_ns(0), m_nc(0), m_nq(0)
- {
- // default maximum speed: 50 rad/s
- m_qmax = 50.0;
- }
- WSDLSSolver::~WSDLSSolver() {
- }
- bool WSDLSSolver::init(unsigned int _nq, unsigned int _nc, const std::vector<bool>& gc)
- {
- if (_nc == 0 || _nq == 0 || gc.size() != _nc)
- return false;
- m_nc = _nc;
- m_nq = _nq;
- m_ns = std::min(m_nc,m_nq);
- m_AWq = e_zero_matrix(m_nc,m_nq);
- m_WyAWq = e_zero_matrix(m_nc,m_nq);
- m_WyAWqt = e_zero_matrix(m_nq,m_nc);
- m_S = e_zero_vector(std::max(m_nc,m_nq));
- m_Wy_ydot = e_zero_vector(m_nc);
- m_ytask = gc;
- if (m_nq > m_nc) {
- m_transpose = true;
- m_temp = e_zero_vector(m_nc);
- m_U = e_zero_matrix(m_nc,m_nc);
- m_V = e_zero_matrix(m_nq,m_nc);
- m_WqV = e_zero_matrix(m_nq,m_nc);
- } else {
- m_transpose = false;
- m_temp = e_zero_vector(m_nq);
- m_U = e_zero_matrix(m_nc,m_nq);
- m_V = e_zero_matrix(m_nq,m_nq);
- m_WqV = e_zero_matrix(m_nq,m_nq);
- }
- return true;
- }
- 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.noalias() = A*Wq;
- 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.array() * ydot.array();
- m_WqV.noalias() = Wq*m_V;
- 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).array().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;
- }
- }
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