111 lines
3.2 KiB
C++
111 lines
3.2 KiB
C++
|
/*
|
||
|
Bullet Continuous Collision Detection and Physics Library
|
||
|
Copyright (c) 2003-2013 Erwin Coumans http://bulletphysics.org
|
||
|
|
||
|
This software is provided 'as-is', without any express or implied warranty.
|
||
|
In no event will the authors be held liable for any damages arising from the use of this software.
|
||
|
Permission is granted to anyone to use this software for any purpose,
|
||
|
including commercial applications, and to alter it and redistribute it freely,
|
||
|
subject to the following restrictions:
|
||
|
|
||
|
1. The origin of this software must not be misrepresented; you must not claim that you wrote the original software. If you use this software in a product, an acknowledgment in the product documentation would be appreciated but is not required.
|
||
|
2. Altered source versions must be plainly marked as such, and must not be misrepresented as being the original software.
|
||
|
3. This notice may not be removed or altered from any source distribution.
|
||
|
*/
|
||
|
///original version written by Erwin Coumans, October 2013
|
||
|
|
||
|
#ifndef BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
|
||
|
#define BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
|
||
|
|
||
|
|
||
|
#include "btMLCPSolverInterface.h"
|
||
|
|
||
|
///This solver is mainly for debug/learning purposes: it is functionally equivalent to the btSequentialImpulseConstraintSolver solver, but much slower (it builds the full LCP matrix)
|
||
|
class btSolveProjectedGaussSeidel : public btMLCPSolverInterface
|
||
|
{
|
||
|
|
||
|
public:
|
||
|
|
||
|
btScalar m_leastSquaresResidualThreshold;
|
||
|
btScalar m_leastSquaresResidual;
|
||
|
|
||
|
btSolveProjectedGaussSeidel()
|
||
|
:m_leastSquaresResidualThreshold(0),
|
||
|
m_leastSquaresResidual(0)
|
||
|
{
|
||
|
}
|
||
|
|
||
|
virtual bool solveMLCP(const btMatrixXu & A, const btVectorXu & b, btVectorXu& x, const btVectorXu & lo,const btVectorXu & hi,const btAlignedObjectArray<int>& limitDependency, int numIterations, bool useSparsity = true)
|
||
|
{
|
||
|
if (!A.rows())
|
||
|
return true;
|
||
|
//the A matrix is sparse, so compute the non-zero elements
|
||
|
A.rowComputeNonZeroElements();
|
||
|
|
||
|
//A is a m-n matrix, m rows, n columns
|
||
|
btAssert(A.rows() == b.rows());
|
||
|
|
||
|
int i, j, numRows = A.rows();
|
||
|
|
||
|
btScalar delta;
|
||
|
|
||
|
for (int k = 0; k <numIterations; k++)
|
||
|
{
|
||
|
m_leastSquaresResidual = 0.f;
|
||
|
for (i = 0; i <numRows; i++)
|
||
|
{
|
||
|
delta = 0.0f;
|
||
|
if (useSparsity)
|
||
|
{
|
||
|
for (int h=0;h<A.m_rowNonZeroElements1[i].size();h++)
|
||
|
{
|
||
|
int j = A.m_rowNonZeroElements1[i][h];
|
||
|
if (j != i)//skip main diagonal
|
||
|
{
|
||
|
delta += A(i,j) * x[j];
|
||
|
}
|
||
|
}
|
||
|
} else
|
||
|
{
|
||
|
for (j = 0; j <i; j++)
|
||
|
delta += A(i,j) * x[j];
|
||
|
for (j = i+1; j<numRows; j++)
|
||
|
delta += A(i,j) * x[j];
|
||
|
}
|
||
|
|
||
|
btScalar aDiag = A(i,i);
|
||
|
btScalar xOld = x[i];
|
||
|
x [i] = (b [i] - delta) / aDiag;
|
||
|
btScalar s = 1.f;
|
||
|
|
||
|
if (limitDependency[i]>=0)
|
||
|
{
|
||
|
s = x[limitDependency[i]];
|
||
|
if (s<0)
|
||
|
s=1;
|
||
|
}
|
||
|
|
||
|
if (x[i]<lo[i]*s)
|
||
|
x[i]=lo[i]*s;
|
||
|
if (x[i]>hi[i]*s)
|
||
|
x[i]=hi[i]*s;
|
||
|
btScalar diff = x[i] - xOld;
|
||
|
m_leastSquaresResidual += diff*diff;
|
||
|
}
|
||
|
|
||
|
btScalar eps = m_leastSquaresResidualThreshold;
|
||
|
if ((m_leastSquaresResidual < eps) || (k >=(numIterations-1)))
|
||
|
{
|
||
|
#ifdef VERBOSE_PRINTF_RESIDUAL
|
||
|
printf("totalLenSqr = %f at iteration #%d\n", m_leastSquaresResidual,k);
|
||
|
#endif
|
||
|
break;
|
||
|
}
|
||
|
}
|
||
|
return true;
|
||
|
}
|
||
|
|
||
|
};
|
||
|
|
||
|
#endif //BT_SOLVE_PROJECTED_GAUSS_SEIDEL_H
|