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- /** \file itasc/WDLSSolver.cpp
- * \ingroup itasc
- */
- /*
- * WDLSSolver.hpp.cpp
- *
- * Created on: Jan 8, 2009
- * Author: rubensmits
- */
- #include "WDLSSolver.hpp"
- #include "kdl/utilities/svd_eigen_HH.hpp"
- namespace iTaSC {
- WDLSSolver::WDLSSolver() : m_lambda(0.5), m_epsilon(0.1)
- {
- // maximum joint velocity
- m_qmax = 50.0;
- }
- WDLSSolver::~WDLSSolver() {
- }
- bool WDLSSolver::init(unsigned int nq, unsigned int nc, const std::vector<bool>& gc)
- {
- m_ns = std::min(nc,nq);
- m_AWq = e_zero_matrix(nc,nq);
- m_WyAWq = e_zero_matrix(nc,nq);
- m_WyAWqt = e_zero_matrix(nq,nc);
- m_S = e_zero_vector(std::max(nc,nq));
- m_Wy_ydot = e_zero_vector(nc);
- if (nq > nc) {
- m_transpose = true;
- m_temp = e_zero_vector(nc);
- m_U = e_zero_matrix(nc,nc);
- m_V = e_zero_matrix(nq,nc);
- m_WqV = e_zero_matrix(nq,nc);
- } else {
- m_transpose = false;
- m_temp = e_zero_vector(nq);
- m_U = e_zero_matrix(nc,nq);
- m_V = e_zero_matrix(nq,nq);
- m_WqV = e_zero_matrix(nq,nq);
- }
- return true;
- }
- bool WDLSSolver::solve(const e_matrix& A, const e_vector& Wy, const e_vector& ydot, const e_matrix& Wq, e_vector& qdot, e_scalar& nlcoef)
- {
- double alpha, vmax, norm;
- // Create the Weighted jacobian
- m_AWq = A*Wq;
- for (int i=0; i<Wy.size(); 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_WqV.noalias() = Wq*m_V;
- //Wy*ydot
- m_Wy_ydot = Wy.array() * ydot.array();
- //S^-1*U'*Wy*ydot
- e_scalar maxDeltaS = e_scalar(0.0);
- e_scalar prevS = e_scalar(0.0);
- e_scalar maxS = e_scalar(1.0);
- e_scalar S, lambda;
- qdot.setZero();
- for(int i=0;i<m_ns;++i) {
- S = m_S(i);
- if (S <= KDL::epsilon)
- break;
- if (i > 0 && (prevS-S) > maxDeltaS) {
- maxDeltaS = (prevS-S);
- maxS = prevS;
- }
- lambda = (S < m_epsilon) ? (e_scalar(1.0)-KDL::sqr(S/m_epsilon))*m_lambda*m_lambda : e_scalar(0.0);
- alpha = m_U.col(i).dot(m_Wy_ydot)*S/(S*S+lambda);
- vmax = m_WqV.col(i).array().abs().maxCoeff();
- norm = fabs(alpha*vmax);
- if (norm > m_qmax) {
- qdot += m_WqV.col(i)*(alpha*m_qmax/norm);
- } else {
- qdot += m_WqV.col(i)*alpha;
- }
- prevS = S;
- }
- if (maxDeltaS == e_scalar(0.0))
- nlcoef = e_scalar(KDL::epsilon);
- else
- nlcoef = (maxS-maxDeltaS)/maxS;
- return true;
- }
- }
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