123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108 |
- /*
- 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++)
- {
- 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
|