103 lines
2.4 KiB
C++
103 lines
2.4 KiB
C++
/* SPDX-FileCopyrightText: 2009 Ruben Smits
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*
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* SPDX-License-Identifier: LGPL-2.1-or-later */
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/** \file
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* \ingroup intern_itasc
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*/
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#include "WDLSSolver.hpp"
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#include "kdl/utilities/svd_eigen_HH.hpp"
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namespace iTaSC {
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WDLSSolver::WDLSSolver() : m_lambda(0.5), m_epsilon(0.1)
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{
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// maximum joint velocity
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m_qmax = 50.0;
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}
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WDLSSolver::~WDLSSolver() {
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}
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bool WDLSSolver::init(unsigned int nq, unsigned int nc, const std::vector<bool>& gc)
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{
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m_ns = std::min(nc,nq);
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m_AWq = e_zero_matrix(nc,nq);
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m_WyAWq = e_zero_matrix(nc,nq);
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m_WyAWqt = e_zero_matrix(nq,nc);
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m_S = e_zero_vector(std::max(nc,nq));
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m_Wy_ydot = e_zero_vector(nc);
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if (nq > nc) {
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m_transpose = true;
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m_temp = e_zero_vector(nc);
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m_U = e_zero_matrix(nc,nc);
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m_V = e_zero_matrix(nq,nc);
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m_WqV = e_zero_matrix(nq,nc);
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} else {
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m_transpose = false;
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m_temp = e_zero_vector(nq);
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m_U = e_zero_matrix(nc,nq);
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m_V = e_zero_matrix(nq,nq);
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m_WqV = e_zero_matrix(nq,nq);
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}
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return true;
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}
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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)
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{
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double alpha, vmax, norm;
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// Create the Weighted jacobian
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m_AWq = A*Wq;
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for (int i=0; i<Wy.size(); i++)
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m_WyAWq.row(i) = Wy(i)*m_AWq.row(i);
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// Compute the SVD of the weighted jacobian
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int ret;
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if (m_transpose) {
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m_WyAWqt = m_WyAWq.transpose();
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ret = KDL::svd_eigen_HH(m_WyAWqt,m_V,m_S,m_U,m_temp);
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} else {
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ret = KDL::svd_eigen_HH(m_WyAWq,m_U,m_S,m_V,m_temp);
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}
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if(ret<0)
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return false;
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m_WqV.noalias() = Wq*m_V;
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//Wy*ydot
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m_Wy_ydot = Wy.array() * ydot.array();
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//S^-1*U'*Wy*ydot
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e_scalar maxDeltaS = e_scalar(0.0);
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e_scalar prevS = e_scalar(0.0);
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e_scalar maxS = e_scalar(1.0);
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e_scalar S, lambda;
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qdot.setZero();
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for(int i=0;i<m_ns;++i) {
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S = m_S(i);
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if (S <= KDL::epsilon)
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break;
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if (i > 0 && (prevS-S) > maxDeltaS) {
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maxDeltaS = (prevS-S);
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maxS = prevS;
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}
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lambda = (S < m_epsilon) ? (e_scalar(1.0)-KDL::sqr(S/m_epsilon))*m_lambda*m_lambda : e_scalar(0.0);
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alpha = m_U.col(i).dot(m_Wy_ydot)*S/(S*S+lambda);
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vmax = m_WqV.col(i).array().abs().maxCoeff();
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norm = fabs(alpha*vmax);
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if (norm > m_qmax) {
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qdot += m_WqV.col(i)*(alpha*m_qmax/norm);
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} else {
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qdot += m_WqV.col(i)*alpha;
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}
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prevS = S;
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}
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if (maxDeltaS == e_scalar(0.0))
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nlcoef = e_scalar(KDL::epsilon);
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else
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nlcoef = (maxS-maxDeltaS)/maxS;
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return true;
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}
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}
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