forked from blender/blender
Campbell Barton
de13d0a80c
While \file doesn't need an argument, it can't have another doxy command after it.
105 lines
2.4 KiB
C++
105 lines
2.4 KiB
C++
/** \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;
|
|
}
|
|
|
|
}
|