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Diffstat (limited to 'thirdparty/bullet/src/BulletDynamics/MLCPSolvers')
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diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.cpp b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.cpp new file mode 100644 index 0000000000..986f214870 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.cpp @@ -0,0 +1,2080 @@ +/************************************************************************* +* * +* Open Dynamics Engine, Copyright (C) 2001,2002 Russell L. Smith. * +* All rights reserved. Email: russ@q12.org Web: www.q12.org * +* * +* This library is free software; you can redistribute it and/or * +* modify it under the terms of EITHER: * +* (1) The GNU Lesser General Public License as published by the Free * +* Software Foundation; either version 2.1 of the License, or (at * +* your option) any later version. The text of the GNU Lesser * +* General Public License is included with this library in the * +* file LICENSE.TXT. * +* (2) The BSD-style license that is included with this library in * +* the file LICENSE-BSD.TXT. * +* * +* This library is distributed in the hope that it will be useful, * +* but WITHOUT ANY WARRANTY; without even the implied warranty of * +* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the files * +* LICENSE.TXT and LICENSE-BSD.TXT for more details. * +* * +*************************************************************************/ + +/* + + +THE ALGORITHM +------------- + +solve A*x = b+w, with x and w subject to certain LCP conditions. +each x(i),w(i) must lie on one of the three line segments in the following +diagram. each line segment corresponds to one index set : + + w(i) + /|\ | : + | | : + | |i in N : + w>0 | |state[i]=0 : + | | : + | | : i in C + w=0 + +-----------------------+ + | : | + | : | + w<0 | : |i in N + | : |state[i]=1 + | : | + | : | + +-------|-----------|-----------|----------> x(i) + lo 0 hi + +the Dantzig algorithm proceeds as follows: + for i=1:n + * if (x(i),w(i)) is not on the line, push x(i) and w(i) positive or + negative towards the line. as this is done, the other (x(j),w(j)) + for j<i are constrained to be on the line. if any (x,w) reaches the + end of a line segment then it is switched between index sets. + * i is added to the appropriate index set depending on what line segment + it hits. + +we restrict lo(i) <= 0 and hi(i) >= 0. this makes the algorithm a bit +simpler, because the starting point for x(i),w(i) is always on the dotted +line x=0 and x will only ever increase in one direction, so it can only hit +two out of the three line segments. + + +NOTES +----- + +this is an implementation of "lcp_dantzig2_ldlt.m" and "lcp_dantzig_lohi.m". +the implementation is split into an LCP problem object (btLCP) and an LCP +driver function. most optimization occurs in the btLCP object. + +a naive implementation of the algorithm requires either a lot of data motion +or a lot of permutation-array lookup, because we are constantly re-ordering +rows and columns. to avoid this and make a more optimized algorithm, a +non-trivial data structure is used to represent the matrix A (this is +implemented in the fast version of the btLCP object). + +during execution of this algorithm, some indexes in A are clamped (set C), +some are non-clamped (set N), and some are "don't care" (where x=0). +A,x,b,w (and other problem vectors) are permuted such that the clamped +indexes are first, the unclamped indexes are next, and the don't-care +indexes are last. this permutation is recorded in the array `p'. +initially p = 0..n-1, and as the rows and columns of A,x,b,w are swapped, +the corresponding elements of p are swapped. + +because the C and N elements are grouped together in the rows of A, we can do +lots of work with a fast dot product function. if A,x,etc were not permuted +and we only had a permutation array, then those dot products would be much +slower as we would have a permutation array lookup in some inner loops. + +A is accessed through an array of row pointers, so that element (i,j) of the +permuted matrix is A[i][j]. this makes row swapping fast. for column swapping +we still have to actually move the data. + +during execution of this algorithm we maintain an L*D*L' factorization of +the clamped submatrix of A (call it `AC') which is the top left nC*nC +submatrix of A. there are two ways we could arrange the rows/columns in AC. + +(1) AC is always permuted such that L*D*L' = AC. this causes a problem +when a row/column is removed from C, because then all the rows/columns of A +between the deleted index and the end of C need to be rotated downward. +this results in a lot of data motion and slows things down. +(2) L*D*L' is actually a factorization of a *permutation* of AC (which is +itself a permutation of the underlying A). this is what we do - the +permutation is recorded in the vector C. call this permutation A[C,C]. +when a row/column is removed from C, all we have to do is swap two +rows/columns and manipulate C. + +*/ + + +#include "btDantzigLCP.h" + +#include <string.h>//memcpy + +bool s_error = false; + +//*************************************************************************** +// code generation parameters + + +#define btLCP_FAST // use fast btLCP object + +// option 1 : matrix row pointers (less data copying) +#define BTROWPTRS +#define BTATYPE btScalar ** +#define BTAROW(i) (m_A[i]) + +// option 2 : no matrix row pointers (slightly faster inner loops) +//#define NOROWPTRS +//#define BTATYPE btScalar * +//#define BTAROW(i) (m_A+(i)*m_nskip) + +#define BTNUB_OPTIMIZATIONS + + + +/* solve L*X=B, with B containing 1 right hand sides. + * L is an n*n lower triangular matrix with ones on the diagonal. + * L is stored by rows and its leading dimension is lskip. + * B is an n*1 matrix that contains the right hand sides. + * B is stored by columns and its leading dimension is also lskip. + * B is overwritten with X. + * this processes blocks of 2*2. + * if this is in the factorizer source file, n must be a multiple of 2. + */ + +static void btSolveL1_1 (const btScalar *L, btScalar *B, int n, int lskip1) +{ + /* declare variables - Z matrix, p and q vectors, etc */ + btScalar Z11,m11,Z21,m21,p1,q1,p2,*ex; + const btScalar *ell; + int i,j; + /* compute all 2 x 1 blocks of X */ + for (i=0; i < n; i+=2) { + /* compute all 2 x 1 block of X, from rows i..i+2-1 */ + /* set the Z matrix to 0 */ + Z11=0; + Z21=0; + ell = L + i*lskip1; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-2; j >= 0; j -= 2) { + /* compute outer product and add it to the Z matrix */ + p1=ell[0]; + q1=ex[0]; + m11 = p1 * q1; + p2=ell[lskip1]; + m21 = p2 * q1; + Z11 += m11; + Z21 += m21; + /* compute outer product and add it to the Z matrix */ + p1=ell[1]; + q1=ex[1]; + m11 = p1 * q1; + p2=ell[1+lskip1]; + m21 = p2 * q1; + /* advance pointers */ + ell += 2; + ex += 2; + Z11 += m11; + Z21 += m21; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 2; + for (; j > 0; j--) { + /* compute outer product and add it to the Z matrix */ + p1=ell[0]; + q1=ex[0]; + m11 = p1 * q1; + p2=ell[lskip1]; + m21 = p2 * q1; + /* advance pointers */ + ell += 1; + ex += 1; + Z11 += m11; + Z21 += m21; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + p1 = ell[lskip1]; + Z21 = ex[1] - Z21 - p1*Z11; + ex[1] = Z21; + /* end of outer loop */ + } +} + +/* solve L*X=B, with B containing 2 right hand sides. + * L is an n*n lower triangular matrix with ones on the diagonal. + * L is stored by rows and its leading dimension is lskip. + * B is an n*2 matrix that contains the right hand sides. + * B is stored by columns and its leading dimension is also lskip. + * B is overwritten with X. + * this processes blocks of 2*2. + * if this is in the factorizer source file, n must be a multiple of 2. + */ + +static void btSolveL1_2 (const btScalar *L, btScalar *B, int n, int lskip1) +{ + /* declare variables - Z matrix, p and q vectors, etc */ + btScalar Z11,m11,Z12,m12,Z21,m21,Z22,m22,p1,q1,p2,q2,*ex; + const btScalar *ell; + int i,j; + /* compute all 2 x 2 blocks of X */ + for (i=0; i < n; i+=2) { + /* compute all 2 x 2 block of X, from rows i..i+2-1 */ + /* set the Z matrix to 0 */ + Z11=0; + Z12=0; + Z21=0; + Z22=0; + ell = L + i*lskip1; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-2; j >= 0; j -= 2) { + /* compute outer product and add it to the Z matrix */ + p1=ell[0]; + q1=ex[0]; + m11 = p1 * q1; + q2=ex[lskip1]; + m12 = p1 * q2; + p2=ell[lskip1]; + m21 = p2 * q1; + m22 = p2 * q2; + Z11 += m11; + Z12 += m12; + Z21 += m21; + Z22 += m22; + /* compute outer product and add it to the Z matrix */ + p1=ell[1]; + q1=ex[1]; + m11 = p1 * q1; + q2=ex[1+lskip1]; + m12 = p1 * q2; + p2=ell[1+lskip1]; + m21 = p2 * q1; + m22 = p2 * q2; + /* advance pointers */ + ell += 2; + ex += 2; + Z11 += m11; + Z12 += m12; + Z21 += m21; + Z22 += m22; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 2; + for (; j > 0; j--) { + /* compute outer product and add it to the Z matrix */ + p1=ell[0]; + q1=ex[0]; + m11 = p1 * q1; + q2=ex[lskip1]; + m12 = p1 * q2; + p2=ell[lskip1]; + m21 = p2 * q1; + m22 = p2 * q2; + /* advance pointers */ + ell += 1; + ex += 1; + Z11 += m11; + Z12 += m12; + Z21 += m21; + Z22 += m22; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + Z12 = ex[lskip1] - Z12; + ex[lskip1] = Z12; + p1 = ell[lskip1]; + Z21 = ex[1] - Z21 - p1*Z11; + ex[1] = Z21; + Z22 = ex[1+lskip1] - Z22 - p1*Z12; + ex[1+lskip1] = Z22; + /* end of outer loop */ + } +} + + +void btFactorLDLT (btScalar *A, btScalar *d, int n, int nskip1) +{ + int i,j; + btScalar sum,*ell,*dee,dd,p1,p2,q1,q2,Z11,m11,Z21,m21,Z22,m22; + if (n < 1) return; + + for (i=0; i<=n-2; i += 2) { + /* solve L*(D*l)=a, l is scaled elements in 2 x i block at A(i,0) */ + btSolveL1_2 (A,A+i*nskip1,i,nskip1); + /* scale the elements in a 2 x i block at A(i,0), and also */ + /* compute Z = the outer product matrix that we'll need. */ + Z11 = 0; + Z21 = 0; + Z22 = 0; + ell = A+i*nskip1; + dee = d; + for (j=i-6; j >= 0; j -= 6) { + p1 = ell[0]; + p2 = ell[nskip1]; + dd = dee[0]; + q1 = p1*dd; + q2 = p2*dd; + ell[0] = q1; + ell[nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + p1 = ell[1]; + p2 = ell[1+nskip1]; + dd = dee[1]; + q1 = p1*dd; + q2 = p2*dd; + ell[1] = q1; + ell[1+nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + p1 = ell[2]; + p2 = ell[2+nskip1]; + dd = dee[2]; + q1 = p1*dd; + q2 = p2*dd; + ell[2] = q1; + ell[2+nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + p1 = ell[3]; + p2 = ell[3+nskip1]; + dd = dee[3]; + q1 = p1*dd; + q2 = p2*dd; + ell[3] = q1; + ell[3+nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + p1 = ell[4]; + p2 = ell[4+nskip1]; + dd = dee[4]; + q1 = p1*dd; + q2 = p2*dd; + ell[4] = q1; + ell[4+nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + p1 = ell[5]; + p2 = ell[5+nskip1]; + dd = dee[5]; + q1 = p1*dd; + q2 = p2*dd; + ell[5] = q1; + ell[5+nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + ell += 6; + dee += 6; + } + /* compute left-over iterations */ + j += 6; + for (; j > 0; j--) { + p1 = ell[0]; + p2 = ell[nskip1]; + dd = dee[0]; + q1 = p1*dd; + q2 = p2*dd; + ell[0] = q1; + ell[nskip1] = q2; + m11 = p1*q1; + m21 = p2*q1; + m22 = p2*q2; + Z11 += m11; + Z21 += m21; + Z22 += m22; + ell++; + dee++; + } + /* solve for diagonal 2 x 2 block at A(i,i) */ + Z11 = ell[0] - Z11; + Z21 = ell[nskip1] - Z21; + Z22 = ell[1+nskip1] - Z22; + dee = d + i; + /* factorize 2 x 2 block Z,dee */ + /* factorize row 1 */ + dee[0] = btRecip(Z11); + /* factorize row 2 */ + sum = 0; + q1 = Z21; + q2 = q1 * dee[0]; + Z21 = q2; + sum += q1*q2; + dee[1] = btRecip(Z22 - sum); + /* done factorizing 2 x 2 block */ + ell[nskip1] = Z21; + } + /* compute the (less than 2) rows at the bottom */ + switch (n-i) { + case 0: + break; + + case 1: + btSolveL1_1 (A,A+i*nskip1,i,nskip1); + /* scale the elements in a 1 x i block at A(i,0), and also */ + /* compute Z = the outer product matrix that we'll need. */ + Z11 = 0; + ell = A+i*nskip1; + dee = d; + for (j=i-6; j >= 0; j -= 6) { + p1 = ell[0]; + dd = dee[0]; + q1 = p1*dd; + ell[0] = q1; + m11 = p1*q1; + Z11 += m11; + p1 = ell[1]; + dd = dee[1]; + q1 = p1*dd; + ell[1] = q1; + m11 = p1*q1; + Z11 += m11; + p1 = ell[2]; + dd = dee[2]; + q1 = p1*dd; + ell[2] = q1; + m11 = p1*q1; + Z11 += m11; + p1 = ell[3]; + dd = dee[3]; + q1 = p1*dd; + ell[3] = q1; + m11 = p1*q1; + Z11 += m11; + p1 = ell[4]; + dd = dee[4]; + q1 = p1*dd; + ell[4] = q1; + m11 = p1*q1; + Z11 += m11; + p1 = ell[5]; + dd = dee[5]; + q1 = p1*dd; + ell[5] = q1; + m11 = p1*q1; + Z11 += m11; + ell += 6; + dee += 6; + } + /* compute left-over iterations */ + j += 6; + for (; j > 0; j--) { + p1 = ell[0]; + dd = dee[0]; + q1 = p1*dd; + ell[0] = q1; + m11 = p1*q1; + Z11 += m11; + ell++; + dee++; + } + /* solve for diagonal 1 x 1 block at A(i,i) */ + Z11 = ell[0] - Z11; + dee = d + i; + /* factorize 1 x 1 block Z,dee */ + /* factorize row 1 */ + dee[0] = btRecip(Z11); + /* done factorizing 1 x 1 block */ + break; + + //default: *((char*)0)=0; /* this should never happen! */ + } +} + +/* solve L*X=B, with B containing 1 right hand sides. + * L is an n*n lower triangular matrix with ones on the diagonal. + * L is stored by rows and its leading dimension is lskip. + * B is an n*1 matrix that contains the right hand sides. + * B is stored by columns and its leading dimension is also lskip. + * B is overwritten with X. + * this processes blocks of 4*4. + * if this is in the factorizer source file, n must be a multiple of 4. + */ + +void btSolveL1 (const btScalar *L, btScalar *B, int n, int lskip1) +{ + /* declare variables - Z matrix, p and q vectors, etc */ + btScalar Z11,Z21,Z31,Z41,p1,q1,p2,p3,p4,*ex; + const btScalar *ell; + int lskip2,lskip3,i,j; + /* compute lskip values */ + lskip2 = 2*lskip1; + lskip3 = 3*lskip1; + /* compute all 4 x 1 blocks of X */ + for (i=0; i <= n-4; i+=4) { + /* compute all 4 x 1 block of X, from rows i..i+4-1 */ + /* set the Z matrix to 0 */ + Z11=0; + Z21=0; + Z31=0; + Z41=0; + ell = L + i*lskip1; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-12; j >= 0; j -= 12) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + p2=ell[lskip1]; + p3=ell[lskip2]; + p4=ell[lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[1]; + q1=ex[1]; + p2=ell[1+lskip1]; + p3=ell[1+lskip2]; + p4=ell[1+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[2]; + q1=ex[2]; + p2=ell[2+lskip1]; + p3=ell[2+lskip2]; + p4=ell[2+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[3]; + q1=ex[3]; + p2=ell[3+lskip1]; + p3=ell[3+lskip2]; + p4=ell[3+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[4]; + q1=ex[4]; + p2=ell[4+lskip1]; + p3=ell[4+lskip2]; + p4=ell[4+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[5]; + q1=ex[5]; + p2=ell[5+lskip1]; + p3=ell[5+lskip2]; + p4=ell[5+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[6]; + q1=ex[6]; + p2=ell[6+lskip1]; + p3=ell[6+lskip2]; + p4=ell[6+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[7]; + q1=ex[7]; + p2=ell[7+lskip1]; + p3=ell[7+lskip2]; + p4=ell[7+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[8]; + q1=ex[8]; + p2=ell[8+lskip1]; + p3=ell[8+lskip2]; + p4=ell[8+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[9]; + q1=ex[9]; + p2=ell[9+lskip1]; + p3=ell[9+lskip2]; + p4=ell[9+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[10]; + q1=ex[10]; + p2=ell[10+lskip1]; + p3=ell[10+lskip2]; + p4=ell[10+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* load p and q values */ + p1=ell[11]; + q1=ex[11]; + p2=ell[11+lskip1]; + p3=ell[11+lskip2]; + p4=ell[11+lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* advance pointers */ + ell += 12; + ex += 12; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 12; + for (; j > 0; j--) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + p2=ell[lskip1]; + p3=ell[lskip2]; + p4=ell[lskip3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + Z21 += p2 * q1; + Z31 += p3 * q1; + Z41 += p4 * q1; + /* advance pointers */ + ell += 1; + ex += 1; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + p1 = ell[lskip1]; + Z21 = ex[1] - Z21 - p1*Z11; + ex[1] = Z21; + p1 = ell[lskip2]; + p2 = ell[1+lskip2]; + Z31 = ex[2] - Z31 - p1*Z11 - p2*Z21; + ex[2] = Z31; + p1 = ell[lskip3]; + p2 = ell[1+lskip3]; + p3 = ell[2+lskip3]; + Z41 = ex[3] - Z41 - p1*Z11 - p2*Z21 - p3*Z31; + ex[3] = Z41; + /* end of outer loop */ + } + /* compute rows at end that are not a multiple of block size */ + for (; i < n; i++) { + /* compute all 1 x 1 block of X, from rows i..i+1-1 */ + /* set the Z matrix to 0 */ + Z11=0; + ell = L + i*lskip1; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-12; j >= 0; j -= 12) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[1]; + q1=ex[1]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[2]; + q1=ex[2]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[3]; + q1=ex[3]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[4]; + q1=ex[4]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[5]; + q1=ex[5]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[6]; + q1=ex[6]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[7]; + q1=ex[7]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[8]; + q1=ex[8]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[9]; + q1=ex[9]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[10]; + q1=ex[10]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* load p and q values */ + p1=ell[11]; + q1=ex[11]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* advance pointers */ + ell += 12; + ex += 12; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 12; + for (; j > 0; j--) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + /* compute outer product and add it to the Z matrix */ + Z11 += p1 * q1; + /* advance pointers */ + ell += 1; + ex += 1; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + } +} + +/* solve L^T * x=b, with b containing 1 right hand side. + * L is an n*n lower triangular matrix with ones on the diagonal. + * L is stored by rows and its leading dimension is lskip. + * b is an n*1 matrix that contains the right hand side. + * b is overwritten with x. + * this processes blocks of 4. + */ + +void btSolveL1T (const btScalar *L, btScalar *B, int n, int lskip1) +{ + /* declare variables - Z matrix, p and q vectors, etc */ + btScalar Z11,m11,Z21,m21,Z31,m31,Z41,m41,p1,q1,p2,p3,p4,*ex; + const btScalar *ell; + int lskip2,i,j; +// int lskip3; + /* special handling for L and B because we're solving L1 *transpose* */ + L = L + (n-1)*(lskip1+1); + B = B + n-1; + lskip1 = -lskip1; + /* compute lskip values */ + lskip2 = 2*lskip1; + //lskip3 = 3*lskip1; + /* compute all 4 x 1 blocks of X */ + for (i=0; i <= n-4; i+=4) { + /* compute all 4 x 1 block of X, from rows i..i+4-1 */ + /* set the Z matrix to 0 */ + Z11=0; + Z21=0; + Z31=0; + Z41=0; + ell = L - i; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-4; j >= 0; j -= 4) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + p2=ell[-1]; + p3=ell[-2]; + p4=ell[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + m21 = p2 * q1; + m31 = p3 * q1; + m41 = p4 * q1; + ell += lskip1; + Z11 += m11; + Z21 += m21; + Z31 += m31; + Z41 += m41; + /* load p and q values */ + p1=ell[0]; + q1=ex[-1]; + p2=ell[-1]; + p3=ell[-2]; + p4=ell[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + m21 = p2 * q1; + m31 = p3 * q1; + m41 = p4 * q1; + ell += lskip1; + Z11 += m11; + Z21 += m21; + Z31 += m31; + Z41 += m41; + /* load p and q values */ + p1=ell[0]; + q1=ex[-2]; + p2=ell[-1]; + p3=ell[-2]; + p4=ell[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + m21 = p2 * q1; + m31 = p3 * q1; + m41 = p4 * q1; + ell += lskip1; + Z11 += m11; + Z21 += m21; + Z31 += m31; + Z41 += m41; + /* load p and q values */ + p1=ell[0]; + q1=ex[-3]; + p2=ell[-1]; + p3=ell[-2]; + p4=ell[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + m21 = p2 * q1; + m31 = p3 * q1; + m41 = p4 * q1; + ell += lskip1; + ex -= 4; + Z11 += m11; + Z21 += m21; + Z31 += m31; + Z41 += m41; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 4; + for (; j > 0; j--) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + p2=ell[-1]; + p3=ell[-2]; + p4=ell[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + m21 = p2 * q1; + m31 = p3 * q1; + m41 = p4 * q1; + ell += lskip1; + ex -= 1; + Z11 += m11; + Z21 += m21; + Z31 += m31; + Z41 += m41; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + p1 = ell[-1]; + Z21 = ex[-1] - Z21 - p1*Z11; + ex[-1] = Z21; + p1 = ell[-2]; + p2 = ell[-2+lskip1]; + Z31 = ex[-2] - Z31 - p1*Z11 - p2*Z21; + ex[-2] = Z31; + p1 = ell[-3]; + p2 = ell[-3+lskip1]; + p3 = ell[-3+lskip2]; + Z41 = ex[-3] - Z41 - p1*Z11 - p2*Z21 - p3*Z31; + ex[-3] = Z41; + /* end of outer loop */ + } + /* compute rows at end that are not a multiple of block size */ + for (; i < n; i++) { + /* compute all 1 x 1 block of X, from rows i..i+1-1 */ + /* set the Z matrix to 0 */ + Z11=0; + ell = L - i; + ex = B; + /* the inner loop that computes outer products and adds them to Z */ + for (j=i-4; j >= 0; j -= 4) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + ell += lskip1; + Z11 += m11; + /* load p and q values */ + p1=ell[0]; + q1=ex[-1]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + ell += lskip1; + Z11 += m11; + /* load p and q values */ + p1=ell[0]; + q1=ex[-2]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + ell += lskip1; + Z11 += m11; + /* load p and q values */ + p1=ell[0]; + q1=ex[-3]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + ell += lskip1; + ex -= 4; + Z11 += m11; + /* end of inner loop */ + } + /* compute left-over iterations */ + j += 4; + for (; j > 0; j--) { + /* load p and q values */ + p1=ell[0]; + q1=ex[0]; + /* compute outer product and add it to the Z matrix */ + m11 = p1 * q1; + ell += lskip1; + ex -= 1; + Z11 += m11; + } + /* finish computing the X(i) block */ + Z11 = ex[0] - Z11; + ex[0] = Z11; + } +} + + + +void btVectorScale (btScalar *a, const btScalar *d, int n) +{ + btAssert (a && d && n >= 0); + for (int i=0; i<n; i++) { + a[i] *= d[i]; + } +} + +void btSolveLDLT (const btScalar *L, const btScalar *d, btScalar *b, int n, int nskip) +{ + btAssert (L && d && b && n > 0 && nskip >= n); + btSolveL1 (L,b,n,nskip); + btVectorScale (b,d,n); + btSolveL1T (L,b,n,nskip); +} + + + +//*************************************************************************** + +// swap row/column i1 with i2 in the n*n matrix A. the leading dimension of +// A is nskip. this only references and swaps the lower triangle. +// if `do_fast_row_swaps' is nonzero and row pointers are being used, then +// rows will be swapped by exchanging row pointers. otherwise the data will +// be copied. + +static void btSwapRowsAndCols (BTATYPE A, int n, int i1, int i2, int nskip, + int do_fast_row_swaps) +{ + btAssert (A && n > 0 && i1 >= 0 && i2 >= 0 && i1 < n && i2 < n && + nskip >= n && i1 < i2); + +# ifdef BTROWPTRS + btScalar *A_i1 = A[i1]; + btScalar *A_i2 = A[i2]; + for (int i=i1+1; i<i2; ++i) { + btScalar *A_i_i1 = A[i] + i1; + A_i1[i] = *A_i_i1; + *A_i_i1 = A_i2[i]; + } + A_i1[i2] = A_i1[i1]; + A_i1[i1] = A_i2[i1]; + A_i2[i1] = A_i2[i2]; + // swap rows, by swapping row pointers + if (do_fast_row_swaps) { + A[i1] = A_i2; + A[i2] = A_i1; + } + else { + // Only swap till i2 column to match A plain storage variant. + for (int k = 0; k <= i2; ++k) { + btScalar tmp = A_i1[k]; + A_i1[k] = A_i2[k]; + A_i2[k] = tmp; + } + } + // swap columns the hard way + for (int j=i2+1; j<n; ++j) { + btScalar *A_j = A[j]; + btScalar tmp = A_j[i1]; + A_j[i1] = A_j[i2]; + A_j[i2] = tmp; + } +# else + btScalar *A_i1 = A+i1*nskip; + btScalar *A_i2 = A+i2*nskip; + for (int k = 0; k < i1; ++k) { + btScalar tmp = A_i1[k]; + A_i1[k] = A_i2[k]; + A_i2[k] = tmp; + } + btScalar *A_i = A_i1 + nskip; + for (int i=i1+1; i<i2; A_i+=nskip, ++i) { + btScalar tmp = A_i2[i]; + A_i2[i] = A_i[i1]; + A_i[i1] = tmp; + } + { + btScalar tmp = A_i1[i1]; + A_i1[i1] = A_i2[i2]; + A_i2[i2] = tmp; + } + btScalar *A_j = A_i2 + nskip; + for (int j=i2+1; j<n; A_j+=nskip, ++j) { + btScalar tmp = A_j[i1]; + A_j[i1] = A_j[i2]; + A_j[i2] = tmp; + } +# endif +} + + +// swap two indexes in the n*n LCP problem. i1 must be <= i2. + +static void btSwapProblem (BTATYPE A, btScalar *x, btScalar *b, btScalar *w, btScalar *lo, + btScalar *hi, int *p, bool *state, int *findex, + int n, int i1, int i2, int nskip, + int do_fast_row_swaps) +{ + btScalar tmpr; + int tmpi; + bool tmpb; + btAssert (n>0 && i1 >=0 && i2 >= 0 && i1 < n && i2 < n && nskip >= n && i1 <= i2); + if (i1==i2) return; + + btSwapRowsAndCols (A,n,i1,i2,nskip,do_fast_row_swaps); + + tmpr = x[i1]; + x[i1] = x[i2]; + x[i2] = tmpr; + + tmpr = b[i1]; + b[i1] = b[i2]; + b[i2] = tmpr; + + tmpr = w[i1]; + w[i1] = w[i2]; + w[i2] = tmpr; + + tmpr = lo[i1]; + lo[i1] = lo[i2]; + lo[i2] = tmpr; + + tmpr = hi[i1]; + hi[i1] = hi[i2]; + hi[i2] = tmpr; + + tmpi = p[i1]; + p[i1] = p[i2]; + p[i2] = tmpi; + + tmpb = state[i1]; + state[i1] = state[i2]; + state[i2] = tmpb; + + if (findex) { + tmpi = findex[i1]; + findex[i1] = findex[i2]; + findex[i2] = tmpi; + } +} + + + + +//*************************************************************************** +// btLCP manipulator object. this represents an n*n LCP problem. +// +// two index sets C and N are kept. each set holds a subset of +// the variable indexes 0..n-1. an index can only be in one set. +// initially both sets are empty. +// +// the index set C is special: solutions to A(C,C)\A(C,i) can be generated. + +//*************************************************************************** +// fast implementation of btLCP. see the above definition of btLCP for +// interface comments. +// +// `p' records the permutation of A,x,b,w,etc. p is initially 1:n and is +// permuted as the other vectors/matrices are permuted. +// +// A,x,b,w,lo,hi,state,findex,p,c are permuted such that sets C,N have +// contiguous indexes. the don't-care indexes follow N. +// +// an L*D*L' factorization is maintained of A(C,C), and whenever indexes are +// added or removed from the set C the factorization is updated. +// thus L*D*L'=A[C,C], i.e. a permuted top left nC*nC submatrix of A. +// the leading dimension of the matrix L is always `nskip'. +// +// at the start there may be other indexes that are unbounded but are not +// included in `nub'. btLCP will permute the matrix so that absolutely all +// unbounded vectors are at the start. thus there may be some initial +// permutation. +// +// the algorithms here assume certain patterns, particularly with respect to +// index transfer. + +#ifdef btLCP_FAST + +struct btLCP +{ + const int m_n; + const int m_nskip; + int m_nub; + int m_nC, m_nN; // size of each index set + BTATYPE const m_A; // A rows + btScalar *const m_x, * const m_b, *const m_w, *const m_lo,* const m_hi; // permuted LCP problem data + btScalar *const m_L, *const m_d; // L*D*L' factorization of set C + btScalar *const m_Dell, *const m_ell, *const m_tmp; + bool *const m_state; + int *const m_findex, *const m_p, *const m_C; + + btLCP (int _n, int _nskip, int _nub, btScalar *_Adata, btScalar *_x, btScalar *_b, btScalar *_w, + btScalar *_lo, btScalar *_hi, btScalar *l, btScalar *_d, + btScalar *_Dell, btScalar *_ell, btScalar *_tmp, + bool *_state, int *_findex, int *p, int *c, btScalar **Arows); + int getNub() const { return m_nub; } + void transfer_i_to_C (int i); + void transfer_i_to_N (int i) { m_nN++; } // because we can assume C and N span 1:i-1 + void transfer_i_from_N_to_C (int i); + void transfer_i_from_C_to_N (int i, btAlignedObjectArray<btScalar>& scratch); + int numC() const { return m_nC; } + int numN() const { return m_nN; } + int indexC (int i) const { return i; } + int indexN (int i) const { return i+m_nC; } + btScalar Aii (int i) const { return BTAROW(i)[i]; } + btScalar AiC_times_qC (int i, btScalar *q) const { return btLargeDot (BTAROW(i), q, m_nC); } + btScalar AiN_times_qN (int i, btScalar *q) const { return btLargeDot (BTAROW(i)+m_nC, q+m_nC, m_nN); } + void pN_equals_ANC_times_qC (btScalar *p, btScalar *q); + void pN_plusequals_ANi (btScalar *p, int i, int sign=1); + void pC_plusequals_s_times_qC (btScalar *p, btScalar s, btScalar *q); + void pN_plusequals_s_times_qN (btScalar *p, btScalar s, btScalar *q); + void solve1 (btScalar *a, int i, int dir=1, int only_transfer=0); + void unpermute(); +}; + + +btLCP::btLCP (int _n, int _nskip, int _nub, btScalar *_Adata, btScalar *_x, btScalar *_b, btScalar *_w, + btScalar *_lo, btScalar *_hi, btScalar *l, btScalar *_d, + btScalar *_Dell, btScalar *_ell, btScalar *_tmp, + bool *_state, int *_findex, int *p, int *c, btScalar **Arows): + m_n(_n), m_nskip(_nskip), m_nub(_nub), m_nC(0), m_nN(0), +# ifdef BTROWPTRS + m_A(Arows), +#else + m_A(_Adata), +#endif + m_x(_x), m_b(_b), m_w(_w), m_lo(_lo), m_hi(_hi), + m_L(l), m_d(_d), m_Dell(_Dell), m_ell(_ell), m_tmp(_tmp), + m_state(_state), m_findex(_findex), m_p(p), m_C(c) +{ + { + btSetZero (m_x,m_n); + } + + { +# ifdef BTROWPTRS + // make matrix row pointers + btScalar *aptr = _Adata; + BTATYPE A = m_A; + const int n = m_n, nskip = m_nskip; + for (int k=0; k<n; aptr+=nskip, ++k) A[k] = aptr; +# endif + } + + { + int *p = m_p; + const int n = m_n; + for (int k=0; k<n; ++k) p[k]=k; // initially unpermuted + } + + /* + // for testing, we can do some random swaps in the area i > nub + { + const int n = m_n; + const int nub = m_nub; + if (nub < n) { + for (int k=0; k<100; k++) { + int i1,i2; + do { + i1 = dRandInt(n-nub)+nub; + i2 = dRandInt(n-nub)+nub; + } + while (i1 > i2); + //printf ("--> %d %d\n",i1,i2); + btSwapProblem (m_A,m_x,m_b,m_w,m_lo,m_hi,m_p,m_state,m_findex,n,i1,i2,m_nskip,0); + } + } + */ + + // permute the problem so that *all* the unbounded variables are at the + // start, i.e. look for unbounded variables not included in `nub'. we can + // potentially push up `nub' this way and get a bigger initial factorization. + // note that when we swap rows/cols here we must not just swap row pointers, + // as the initial factorization relies on the data being all in one chunk. + // variables that have findex >= 0 are *not* considered to be unbounded even + // if lo=-inf and hi=inf - this is because these limits may change during the + // solution process. + + { + int *findex = m_findex; + btScalar *lo = m_lo, *hi = m_hi; + const int n = m_n; + for (int k = m_nub; k<n; ++k) { + if (findex && findex[k] >= 0) continue; + if (lo[k]==-BT_INFINITY && hi[k]==BT_INFINITY) { + btSwapProblem (m_A,m_x,m_b,m_w,lo,hi,m_p,m_state,findex,n,m_nub,k,m_nskip,0); + m_nub++; + } + } + } + + // if there are unbounded variables at the start, factorize A up to that + // point and solve for x. this puts all indexes 0..nub-1 into C. + if (m_nub > 0) { + const int nub = m_nub; + { + btScalar *Lrow = m_L; + const int nskip = m_nskip; + for (int j=0; j<nub; Lrow+=nskip, ++j) memcpy(Lrow,BTAROW(j),(j+1)*sizeof(btScalar)); + } + btFactorLDLT (m_L,m_d,nub,m_nskip); + memcpy (m_x,m_b,nub*sizeof(btScalar)); + btSolveLDLT (m_L,m_d,m_x,nub,m_nskip); + btSetZero (m_w,nub); + { + int *C = m_C; + for (int k=0; k<nub; ++k) C[k] = k; + } + m_nC = nub; + } + + // permute the indexes > nub such that all findex variables are at the end + if (m_findex) { + const int nub = m_nub; + int *findex = m_findex; + int num_at_end = 0; + for (int k=m_n-1; k >= nub; k--) { + if (findex[k] >= 0) { + btSwapProblem (m_A,m_x,m_b,m_w,m_lo,m_hi,m_p,m_state,findex,m_n,k,m_n-1-num_at_end,m_nskip,1); + num_at_end++; + } + } + } + + // print info about indexes + /* + { + const int n = m_n; + const int nub = m_nub; + for (int k=0; k<n; k++) { + if (k<nub) printf ("C"); + else if (m_lo[k]==-BT_INFINITY && m_hi[k]==BT_INFINITY) printf ("c"); + else printf ("."); + } + printf ("\n"); + } + */ +} + + +void btLCP::transfer_i_to_C (int i) +{ + { + if (m_nC > 0) { + // ell,Dell were computed by solve1(). note, ell = D \ L1solve (L,A(i,C)) + { + const int nC = m_nC; + btScalar *const Ltgt = m_L + nC*m_nskip, *ell = m_ell; + for (int j=0; j<nC; ++j) Ltgt[j] = ell[j]; + } + const int nC = m_nC; + m_d[nC] = btRecip (BTAROW(i)[i] - btLargeDot(m_ell,m_Dell,nC)); + } + else { + m_d[0] = btRecip (BTAROW(i)[i]); + } + + btSwapProblem (m_A,m_x,m_b,m_w,m_lo,m_hi,m_p,m_state,m_findex,m_n,m_nC,i,m_nskip,1); + + const int nC = m_nC; + m_C[nC] = nC; + m_nC = nC + 1; // nC value is outdated after this line + } + +} + + +void btLCP::transfer_i_from_N_to_C (int i) +{ + { + if (m_nC > 0) { + { + btScalar *const aptr = BTAROW(i); + btScalar *Dell = m_Dell; + const int *C = m_C; +# ifdef BTNUB_OPTIMIZATIONS + // if nub>0, initial part of aptr unpermuted + const int nub = m_nub; + int j=0; + for ( ; j<nub; ++j) Dell[j] = aptr[j]; + const int nC = m_nC; + for ( ; j<nC; ++j) Dell[j] = aptr[C[j]]; +# else + const int nC = m_nC; + for (int j=0; j<nC; ++j) Dell[j] = aptr[C[j]]; +# endif + } + btSolveL1 (m_L,m_Dell,m_nC,m_nskip); + { + const int nC = m_nC; + btScalar *const Ltgt = m_L + nC*m_nskip; + btScalar *ell = m_ell, *Dell = m_Dell, *d = m_d; + for (int j=0; j<nC; ++j) Ltgt[j] = ell[j] = Dell[j] * d[j]; + } + const int nC = m_nC; + m_d[nC] = btRecip (BTAROW(i)[i] - btLargeDot(m_ell,m_Dell,nC)); + } + else { + m_d[0] = btRecip (BTAROW(i)[i]); + } + + btSwapProblem (m_A,m_x,m_b,m_w,m_lo,m_hi,m_p,m_state,m_findex,m_n,m_nC,i,m_nskip,1); + + const int nC = m_nC; + m_C[nC] = nC; + m_nN--; + m_nC = nC + 1; // nC value is outdated after this line + } + + // @@@ TO DO LATER + // if we just finish here then we'll go back and re-solve for + // delta_x. but actually we can be more efficient and incrementally + // update delta_x here. but if we do this, we wont have ell and Dell + // to use in updating the factorization later. + +} + +void btRemoveRowCol (btScalar *A, int n, int nskip, int r) +{ + btAssert(A && n > 0 && nskip >= n && r >= 0 && r < n); + if (r >= n-1) return; + if (r > 0) { + { + const size_t move_size = (n-r-1)*sizeof(btScalar); + btScalar *Adst = A + r; + for (int i=0; i<r; Adst+=nskip,++i) { + btScalar *Asrc = Adst + 1; + memmove (Adst,Asrc,move_size); + } + } + { + const size_t cpy_size = r*sizeof(btScalar); + btScalar *Adst = A + r * nskip; + for (int i=r; i<(n-1); ++i) { + btScalar *Asrc = Adst + nskip; + memcpy (Adst,Asrc,cpy_size); + Adst = Asrc; + } + } + } + { + const size_t cpy_size = (n-r-1)*sizeof(btScalar); + btScalar *Adst = A + r * (nskip + 1); + for (int i=r; i<(n-1); ++i) { + btScalar *Asrc = Adst + (nskip + 1); + memcpy (Adst,Asrc,cpy_size); + Adst = Asrc - 1; + } + } +} + + + + +void btLDLTAddTL (btScalar *L, btScalar *d, const btScalar *a, int n, int nskip, btAlignedObjectArray<btScalar>& scratch) +{ + btAssert (L && d && a && n > 0 && nskip >= n); + + if (n < 2) return; + scratch.resize(2*nskip); + btScalar *W1 = &scratch[0]; + + btScalar *W2 = W1 + nskip; + + W1[0] = btScalar(0.0); + W2[0] = btScalar(0.0); + for (int j=1; j<n; ++j) { + W1[j] = W2[j] = (btScalar) (a[j] * SIMDSQRT12); + } + btScalar W11 = (btScalar) ((btScalar(0.5)*a[0]+1)*SIMDSQRT12); + btScalar W21 = (btScalar) ((btScalar(0.5)*a[0]-1)*SIMDSQRT12); + + btScalar alpha1 = btScalar(1.0); + btScalar alpha2 = btScalar(1.0); + + { + btScalar dee = d[0]; + btScalar alphanew = alpha1 + (W11*W11)*dee; + btAssert(alphanew != btScalar(0.0)); + dee /= alphanew; + btScalar gamma1 = W11 * dee; + dee *= alpha1; + alpha1 = alphanew; + alphanew = alpha2 - (W21*W21)*dee; + dee /= alphanew; + //btScalar gamma2 = W21 * dee; + alpha2 = alphanew; + btScalar k1 = btScalar(1.0) - W21*gamma1; + btScalar k2 = W21*gamma1*W11 - W21; + btScalar *ll = L + nskip; + for (int p=1; p<n; ll+=nskip, ++p) { + btScalar Wp = W1[p]; + btScalar ell = *ll; + W1[p] = Wp - W11*ell; + W2[p] = k1*Wp + k2*ell; + } + } + + btScalar *ll = L + (nskip + 1); + for (int j=1; j<n; ll+=nskip+1, ++j) { + btScalar k1 = W1[j]; + btScalar k2 = W2[j]; + + btScalar dee = d[j]; + btScalar alphanew = alpha1 + (k1*k1)*dee; + btAssert(alphanew != btScalar(0.0)); + dee /= alphanew; + btScalar gamma1 = k1 * dee; + dee *= alpha1; + alpha1 = alphanew; + alphanew = alpha2 - (k2*k2)*dee; + dee /= alphanew; + btScalar gamma2 = k2 * dee; + dee *= alpha2; + d[j] = dee; + alpha2 = alphanew; + + btScalar *l = ll + nskip; + for (int p=j+1; p<n; l+=nskip, ++p) { + btScalar ell = *l; + btScalar Wp = W1[p] - k1 * ell; + ell += gamma1 * Wp; + W1[p] = Wp; + Wp = W2[p] - k2 * ell; + ell -= gamma2 * Wp; + W2[p] = Wp; + *l = ell; + } + } +} + + +#define _BTGETA(i,j) (A[i][j]) +//#define _GETA(i,j) (A[(i)*nskip+(j)]) +#define BTGETA(i,j) ((i > j) ? _BTGETA(i,j) : _BTGETA(j,i)) + +inline size_t btEstimateLDLTAddTLTmpbufSize(int nskip) +{ + return nskip * 2 * sizeof(btScalar); +} + + +void btLDLTRemove (btScalar **A, const int *p, btScalar *L, btScalar *d, + int n1, int n2, int r, int nskip, btAlignedObjectArray<btScalar>& scratch) +{ + btAssert(A && p && L && d && n1 > 0 && n2 > 0 && r >= 0 && r < n2 && + n1 >= n2 && nskip >= n1); + #ifdef BT_DEBUG + for (int i=0; i<n2; ++i) + btAssert(p[i] >= 0 && p[i] < n1); + #endif + + if (r==n2-1) { + return; // deleting last row/col is easy + } + else { + size_t LDLTAddTL_size = btEstimateLDLTAddTLTmpbufSize(nskip); + btAssert(LDLTAddTL_size % sizeof(btScalar) == 0); + scratch.resize(nskip * 2+n2); + btScalar *tmp = &scratch[0]; + if (r==0) { + btScalar *a = (btScalar *)((char *)tmp + LDLTAddTL_size); + const int p_0 = p[0]; + for (int i=0; i<n2; ++i) { + a[i] = -BTGETA(p[i],p_0); + } + a[0] += btScalar(1.0); + btLDLTAddTL (L,d,a,n2,nskip,scratch); + } + else { + btScalar *t = (btScalar *)((char *)tmp + LDLTAddTL_size); + { + btScalar *Lcurr = L + r*nskip; + for (int i=0; i<r; ++Lcurr, ++i) { + btAssert(d[i] != btScalar(0.0)); + t[i] = *Lcurr / d[i]; + } + } + btScalar *a = t + r; + { + btScalar *Lcurr = L + r*nskip; + const int *pp_r = p + r, p_r = *pp_r; + const int n2_minus_r = n2-r; + for (int i=0; i<n2_minus_r; Lcurr+=nskip,++i) { + a[i] = btLargeDot(Lcurr,t,r) - BTGETA(pp_r[i],p_r); + } + } + a[0] += btScalar(1.0); + btLDLTAddTL (L + r*nskip+r, d+r, a, n2-r, nskip, scratch); + } + } + + // snip out row/column r from L and d + btRemoveRowCol (L,n2,nskip,r); + if (r < (n2-1)) memmove (d+r,d+r+1,(n2-r-1)*sizeof(btScalar)); +} + + +void btLCP::transfer_i_from_C_to_N (int i, btAlignedObjectArray<btScalar>& scratch) +{ + { + int *C = m_C; + // remove a row/column from the factorization, and adjust the + // indexes (black magic!) + int last_idx = -1; + const int nC = m_nC; + int j = 0; + for ( ; j<nC; ++j) { + if (C[j]==nC-1) { + last_idx = j; + } + if (C[j]==i) { + btLDLTRemove (m_A,C,m_L,m_d,m_n,nC,j,m_nskip,scratch); + int k; + if (last_idx == -1) { + for (k=j+1 ; k<nC; ++k) { + if (C[k]==nC-1) { + break; + } + } + btAssert (k < nC); + } + else { + k = last_idx; + } + C[k] = C[j]; + if (j < (nC-1)) memmove (C+j,C+j+1,(nC-j-1)*sizeof(int)); + break; + } + } + btAssert (j < nC); + + btSwapProblem (m_A,m_x,m_b,m_w,m_lo,m_hi,m_p,m_state,m_findex,m_n,i,nC-1,m_nskip,1); + + m_nN++; + m_nC = nC - 1; // nC value is outdated after this line + } + +} + + +void btLCP::pN_equals_ANC_times_qC (btScalar *p, btScalar *q) +{ + // we could try to make this matrix-vector multiplication faster using + // outer product matrix tricks, e.g. with the dMultidotX() functions. + // but i tried it and it actually made things slower on random 100x100 + // problems because of the overhead involved. so we'll stick with the + // simple method for now. + const int nC = m_nC; + btScalar *ptgt = p + nC; + const int nN = m_nN; + for (int i=0; i<nN; ++i) { + ptgt[i] = btLargeDot (BTAROW(i+nC),q,nC); + } +} + + +void btLCP::pN_plusequals_ANi (btScalar *p, int i, int sign) +{ + const int nC = m_nC; + btScalar *aptr = BTAROW(i) + nC; + btScalar *ptgt = p + nC; + if (sign > 0) { + const int nN = m_nN; + for (int j=0; j<nN; ++j) ptgt[j] += aptr[j]; + } + else { + const int nN = m_nN; + for (int j=0; j<nN; ++j) ptgt[j] -= aptr[j]; + } +} + +void btLCP::pC_plusequals_s_times_qC (btScalar *p, btScalar s, btScalar *q) +{ + const int nC = m_nC; + for (int i=0; i<nC; ++i) { + p[i] += s*q[i]; + } +} + +void btLCP::pN_plusequals_s_times_qN (btScalar *p, btScalar s, btScalar *q) +{ + const int nC = m_nC; + btScalar *ptgt = p + nC, *qsrc = q + nC; + const int nN = m_nN; + for (int i=0; i<nN; ++i) { + ptgt[i] += s*qsrc[i]; + } +} + +void btLCP::solve1 (btScalar *a, int i, int dir, int only_transfer) +{ + // the `Dell' and `ell' that are computed here are saved. if index i is + // later added to the factorization then they can be reused. + // + // @@@ question: do we need to solve for entire delta_x??? yes, but + // only if an x goes below 0 during the step. + + if (m_nC > 0) { + { + btScalar *Dell = m_Dell; + int *C = m_C; + btScalar *aptr = BTAROW(i); +# ifdef BTNUB_OPTIMIZATIONS + // if nub>0, initial part of aptr[] is guaranteed unpermuted + const int nub = m_nub; + int j=0; + for ( ; j<nub; ++j) Dell[j] = aptr[j]; + const int nC = m_nC; + for ( ; j<nC; ++j) Dell[j] = aptr[C[j]]; +# else + const int nC = m_nC; + for (int j=0; j<nC; ++j) Dell[j] = aptr[C[j]]; +# endif + } + btSolveL1 (m_L,m_Dell,m_nC,m_nskip); + { + btScalar *ell = m_ell, *Dell = m_Dell, *d = m_d; + const int nC = m_nC; + for (int j=0; j<nC; ++j) ell[j] = Dell[j] * d[j]; + } + + if (!only_transfer) { + btScalar *tmp = m_tmp, *ell = m_ell; + { + const int nC = m_nC; + for (int j=0; j<nC; ++j) tmp[j] = ell[j]; + } + btSolveL1T (m_L,tmp,m_nC,m_nskip); + if (dir > 0) { + int *C = m_C; + btScalar *tmp = m_tmp; + const int nC = m_nC; + for (int j=0; j<nC; ++j) a[C[j]] = -tmp[j]; + } else { + int *C = m_C; + btScalar *tmp = m_tmp; + const int nC = m_nC; + for (int j=0; j<nC; ++j) a[C[j]] = tmp[j]; + } + } + } +} + + +void btLCP::unpermute() +{ + // now we have to un-permute x and w + { + memcpy (m_tmp,m_x,m_n*sizeof(btScalar)); + btScalar *x = m_x, *tmp = m_tmp; + const int *p = m_p; + const int n = m_n; + for (int j=0; j<n; ++j) x[p[j]] = tmp[j]; + } + { + memcpy (m_tmp,m_w,m_n*sizeof(btScalar)); + btScalar *w = m_w, *tmp = m_tmp; + const int *p = m_p; + const int n = m_n; + for (int j=0; j<n; ++j) w[p[j]] = tmp[j]; + } +} + +#endif // btLCP_FAST + + +//*************************************************************************** +// an optimized Dantzig LCP driver routine for the lo-hi LCP problem. + +bool btSolveDantzigLCP (int n, btScalar *A, btScalar *x, btScalar *b, + btScalar* outer_w, int nub, btScalar *lo, btScalar *hi, int *findex, btDantzigScratchMemory& scratchMem) +{ + s_error = false; + +// printf("btSolveDantzigLCP n=%d\n",n); + btAssert (n>0 && A && x && b && lo && hi && nub >= 0 && nub <= n); + btAssert(outer_w); + +#ifdef BT_DEBUG + { + // check restrictions on lo and hi + for (int k=0; k<n; ++k) + btAssert (lo[k] <= 0 && hi[k] >= 0); + } +# endif + + + // if all the variables are unbounded then we can just factor, solve, + // and return + if (nub >= n) + { + + + int nskip = (n); + btFactorLDLT (A, outer_w, n, nskip); + btSolveLDLT (A, outer_w, b, n, nskip); + memcpy (x, b, n*sizeof(btScalar)); + + return !s_error; + } + + const int nskip = (n); + scratchMem.L.resize(n*nskip); + + scratchMem.d.resize(n); + + btScalar *w = outer_w; + scratchMem.delta_w.resize(n); + scratchMem.delta_x.resize(n); + scratchMem.Dell.resize(n); + scratchMem.ell.resize(n); + scratchMem.Arows.resize(n); + scratchMem.p.resize(n); + scratchMem.C.resize(n); + + // for i in N, state[i] is 0 if x(i)==lo(i) or 1 if x(i)==hi(i) + scratchMem.state.resize(n); + + + // create LCP object. note that tmp is set to delta_w to save space, this + // optimization relies on knowledge of how tmp is used, so be careful! + btLCP lcp(n,nskip,nub,A,x,b,w,lo,hi,&scratchMem.L[0],&scratchMem.d[0],&scratchMem.Dell[0],&scratchMem.ell[0],&scratchMem.delta_w[0],&scratchMem.state[0],findex,&scratchMem.p[0],&scratchMem.C[0],&scratchMem.Arows[0]); + int adj_nub = lcp.getNub(); + + // loop over all indexes adj_nub..n-1. for index i, if x(i),w(i) satisfy the + // LCP conditions then i is added to the appropriate index set. otherwise + // x(i),w(i) is driven either +ve or -ve to force it to the valid region. + // as we drive x(i), x(C) is also adjusted to keep w(C) at zero. + // while driving x(i) we maintain the LCP conditions on the other variables + // 0..i-1. we do this by watching out for other x(i),w(i) values going + // outside the valid region, and then switching them between index sets + // when that happens. + + bool hit_first_friction_index = false; + for (int i=adj_nub; i<n; ++i) + { + s_error = false; + // the index i is the driving index and indexes i+1..n-1 are "dont care", + // i.e. when we make changes to the system those x's will be zero and we + // don't care what happens to those w's. in other words, we only consider + // an (i+1)*(i+1) sub-problem of A*x=b+w. + + // if we've hit the first friction index, we have to compute the lo and + // hi values based on the values of x already computed. we have been + // permuting the indexes, so the values stored in the findex vector are + // no longer valid. thus we have to temporarily unpermute the x vector. + // for the purposes of this computation, 0*infinity = 0 ... so if the + // contact constraint's normal force is 0, there should be no tangential + // force applied. + + if (!hit_first_friction_index && findex && findex[i] >= 0) { + // un-permute x into delta_w, which is not being used at the moment + for (int j=0; j<n; ++j) scratchMem.delta_w[scratchMem.p[j]] = x[j]; + + // set lo and hi values + for (int k=i; k<n; ++k) { + btScalar wfk = scratchMem.delta_w[findex[k]]; + if (wfk == 0) { + hi[k] = 0; + lo[k] = 0; + } + else { + hi[k] = btFabs (hi[k] * wfk); + lo[k] = -hi[k]; + } + } + hit_first_friction_index = true; + } + + // thus far we have not even been computing the w values for indexes + // greater than i, so compute w[i] now. + w[i] = lcp.AiC_times_qC (i,x) + lcp.AiN_times_qN (i,x) - b[i]; + + // if lo=hi=0 (which can happen for tangential friction when normals are + // 0) then the index will be assigned to set N with some state. however, + // set C's line has zero size, so the index will always remain in set N. + // with the "normal" switching logic, if w changed sign then the index + // would have to switch to set C and then back to set N with an inverted + // state. this is pointless, and also computationally expensive. to + // prevent this from happening, we use the rule that indexes with lo=hi=0 + // will never be checked for set changes. this means that the state for + // these indexes may be incorrect, but that doesn't matter. + + // see if x(i),w(i) is in a valid region + if (lo[i]==0 && w[i] >= 0) { + lcp.transfer_i_to_N (i); + scratchMem.state[i] = false; + } + else if (hi[i]==0 && w[i] <= 0) { + lcp.transfer_i_to_N (i); + scratchMem.state[i] = true; + } + else if (w[i]==0) { + // this is a degenerate case. by the time we get to this test we know + // that lo != 0, which means that lo < 0 as lo is not allowed to be +ve, + // and similarly that hi > 0. this means that the line segment + // corresponding to set C is at least finite in extent, and we are on it. + // NOTE: we must call lcp.solve1() before lcp.transfer_i_to_C() + lcp.solve1 (&scratchMem.delta_x[0],i,0,1); + + lcp.transfer_i_to_C (i); + } + else { + // we must push x(i) and w(i) + for (;;) { + int dir; + btScalar dirf; + // find direction to push on x(i) + if (w[i] <= 0) { + dir = 1; + dirf = btScalar(1.0); + } + else { + dir = -1; + dirf = btScalar(-1.0); + } + + // compute: delta_x(C) = -dir*A(C,C)\A(C,i) + lcp.solve1 (&scratchMem.delta_x[0],i,dir); + + // note that delta_x[i] = dirf, but we wont bother to set it + + // compute: delta_w = A*delta_x ... note we only care about + // delta_w(N) and delta_w(i), the rest is ignored + lcp.pN_equals_ANC_times_qC (&scratchMem.delta_w[0],&scratchMem.delta_x[0]); + lcp.pN_plusequals_ANi (&scratchMem.delta_w[0],i,dir); + scratchMem.delta_w[i] = lcp.AiC_times_qC (i,&scratchMem.delta_x[0]) + lcp.Aii(i)*dirf; + + // find largest step we can take (size=s), either to drive x(i),w(i) + // to the valid LCP region or to drive an already-valid variable + // outside the valid region. + + int cmd = 1; // index switching command + int si = 0; // si = index to switch if cmd>3 + btScalar s = -w[i]/scratchMem.delta_w[i]; + if (dir > 0) { + if (hi[i] < BT_INFINITY) { + btScalar s2 = (hi[i]-x[i])*dirf; // was (hi[i]-x[i])/dirf // step to x(i)=hi(i) + if (s2 < s) { + s = s2; + cmd = 3; + } + } + } + else { + if (lo[i] > -BT_INFINITY) { + btScalar s2 = (lo[i]-x[i])*dirf; // was (lo[i]-x[i])/dirf // step to x(i)=lo(i) + if (s2 < s) { + s = s2; + cmd = 2; + } + } + } + + { + const int numN = lcp.numN(); + for (int k=0; k < numN; ++k) { + const int indexN_k = lcp.indexN(k); + if (!scratchMem.state[indexN_k] ? scratchMem.delta_w[indexN_k] < 0 : scratchMem.delta_w[indexN_k] > 0) { + // don't bother checking if lo=hi=0 + if (lo[indexN_k] == 0 && hi[indexN_k] == 0) continue; + btScalar s2 = -w[indexN_k] / scratchMem.delta_w[indexN_k]; + if (s2 < s) { + s = s2; + cmd = 4; + si = indexN_k; + } + } + } + } + + { + const int numC = lcp.numC(); + for (int k=adj_nub; k < numC; ++k) { + const int indexC_k = lcp.indexC(k); + if (scratchMem.delta_x[indexC_k] < 0 && lo[indexC_k] > -BT_INFINITY) { + btScalar s2 = (lo[indexC_k]-x[indexC_k]) / scratchMem.delta_x[indexC_k]; + if (s2 < s) { + s = s2; + cmd = 5; + si = indexC_k; + } + } + if (scratchMem.delta_x[indexC_k] > 0 && hi[indexC_k] < BT_INFINITY) { + btScalar s2 = (hi[indexC_k]-x[indexC_k]) / scratchMem.delta_x[indexC_k]; + if (s2 < s) { + s = s2; + cmd = 6; + si = indexC_k; + } + } + } + } + + //static char* cmdstring[8] = {0,"->C","->NL","->NH","N->C", + // "C->NL","C->NH"}; + //printf ("cmd=%d (%s), si=%d\n",cmd,cmdstring[cmd],(cmd>3) ? si : i); + + // if s <= 0 then we've got a problem. if we just keep going then + // we're going to get stuck in an infinite loop. instead, just cross + // our fingers and exit with the current solution. + if (s <= btScalar(0.0)) + { +// printf("LCP internal error, s <= 0 (s=%.4e)",(double)s); + if (i < n) { + btSetZero (x+i,n-i); + btSetZero (w+i,n-i); + } + s_error = true; + break; + } + + // apply x = x + s * delta_x + lcp.pC_plusequals_s_times_qC (x, s, &scratchMem.delta_x[0]); + x[i] += s * dirf; + + // apply w = w + s * delta_w + lcp.pN_plusequals_s_times_qN (w, s, &scratchMem.delta_w[0]); + w[i] += s * scratchMem.delta_w[i]; + +// void *tmpbuf; + // switch indexes between sets if necessary + switch (cmd) { + case 1: // done + w[i] = 0; + lcp.transfer_i_to_C (i); + break; + case 2: // done + x[i] = lo[i]; + scratchMem.state[i] = false; + lcp.transfer_i_to_N (i); + break; + case 3: // done + x[i] = hi[i]; + scratchMem.state[i] = true; + lcp.transfer_i_to_N (i); + break; + case 4: // keep going + w[si] = 0; + lcp.transfer_i_from_N_to_C (si); + break; + case 5: // keep going + x[si] = lo[si]; + scratchMem.state[si] = false; + lcp.transfer_i_from_C_to_N (si, scratchMem.m_scratch); + break; + case 6: // keep going + x[si] = hi[si]; + scratchMem.state[si] = true; + lcp.transfer_i_from_C_to_N (si, scratchMem.m_scratch); + break; + } + + if (cmd <= 3) break; + } // for (;;) + } // else + + if (s_error) + { + break; + } + } // for (int i=adj_nub; i<n; ++i) + + lcp.unpermute(); + + + return !s_error; +} + diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.h new file mode 100644 index 0000000000..903832770a --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigLCP.h @@ -0,0 +1,77 @@ +/************************************************************************* + * * + * Open Dynamics Engine, Copyright (C) 2001,2002 Russell L. Smith. * + * All rights reserved. Email: russ@q12.org Web: www.q12.org * + * * + * This library is free software; you can redistribute it and/or * + * modify it under the terms of * + * The BSD-style license that is included with this library in * + * the file LICENSE-BSD.TXT. * + * * + * This library is distributed in the hope that it will be useful, * + * but WITHOUT ANY WARRANTY; without even the implied warranty of * + * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the files * + * LICENSE.TXT and LICENSE-BSD.TXT for more details. * + * * + *************************************************************************/ + +/* + +given (A,b,lo,hi), solve the LCP problem: A*x = b+w, where each x(i),w(i) +satisfies one of + (1) x = lo, w >= 0 + (2) x = hi, w <= 0 + (3) lo < x < hi, w = 0 +A is a matrix of dimension n*n, everything else is a vector of size n*1. +lo and hi can be +/- dInfinity as needed. the first `nub' variables are +unbounded, i.e. hi and lo are assumed to be +/- dInfinity. + +we restrict lo(i) <= 0 and hi(i) >= 0. + +the original data (A,b) may be modified by this function. + +if the `findex' (friction index) parameter is nonzero, it points to an array +of index values. in this case constraints that have findex[i] >= 0 are +special. all non-special constraints are solved for, then the lo and hi values +for the special constraints are set: + hi[i] = abs( hi[i] * x[findex[i]] ) + lo[i] = -hi[i] +and the solution continues. this mechanism allows a friction approximation +to be implemented. the first `nub' variables are assumed to have findex < 0. + +*/ + + +#ifndef _BT_LCP_H_ +#define _BT_LCP_H_ + +#include <stdlib.h> +#include <stdio.h> +#include <assert.h> + + +#include "LinearMath/btScalar.h" +#include "LinearMath/btAlignedObjectArray.h" + +struct btDantzigScratchMemory +{ + btAlignedObjectArray<btScalar> m_scratch; + btAlignedObjectArray<btScalar> L; + btAlignedObjectArray<btScalar> d; + btAlignedObjectArray<btScalar> delta_w; + btAlignedObjectArray<btScalar> delta_x; + btAlignedObjectArray<btScalar> Dell; + btAlignedObjectArray<btScalar> ell; + btAlignedObjectArray<btScalar*> Arows; + btAlignedObjectArray<int> p; + btAlignedObjectArray<int> C; + btAlignedObjectArray<bool> state; +}; + +//return false if solving failed +bool btSolveDantzigLCP (int n, btScalar *A, btScalar *x, btScalar *b, btScalar *w, + int nub, btScalar *lo, btScalar *hi, int *findex,btDantzigScratchMemory& scratch); + + + +#endif //_BT_LCP_H_ diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigSolver.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigSolver.h new file mode 100644 index 0000000000..2a2f2d3d32 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btDantzigSolver.h @@ -0,0 +1,112 @@ +/* +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_DANTZIG_SOLVER_H +#define BT_DANTZIG_SOLVER_H + +#include "btMLCPSolverInterface.h" +#include "btDantzigLCP.h" + + +class btDantzigSolver : public btMLCPSolverInterface +{ +protected: + + btScalar m_acceptableUpperLimitSolution; + + btAlignedObjectArray<char> m_tempBuffer; + + btAlignedObjectArray<btScalar> m_A; + btAlignedObjectArray<btScalar> m_b; + btAlignedObjectArray<btScalar> m_x; + btAlignedObjectArray<btScalar> m_lo; + btAlignedObjectArray<btScalar> m_hi; + btAlignedObjectArray<int> m_dependencies; + btDantzigScratchMemory m_scratchMemory; +public: + + btDantzigSolver() + :m_acceptableUpperLimitSolution(btScalar(1000)) + { + } + + 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) + { + bool result = true; + int n = b.rows(); + if (n) + { + int nub = 0; + btAlignedObjectArray<btScalar> ww; + ww.resize(n); + + + const btScalar* Aptr = A.getBufferPointer(); + m_A.resize(n*n); + for (int i=0;i<n*n;i++) + { + m_A[i] = Aptr[i]; + + } + + m_b.resize(n); + m_x.resize(n); + m_lo.resize(n); + m_hi.resize(n); + m_dependencies.resize(n); + for (int i=0;i<n;i++) + { + m_lo[i] = lo[i]; + m_hi[i] = hi[i]; + m_b[i] = b[i]; + m_x[i] = x[i]; + m_dependencies[i] = limitDependency[i]; + } + + + result = btSolveDantzigLCP (n,&m_A[0],&m_x[0],&m_b[0],&ww[0],nub,&m_lo[0],&m_hi[0],&m_dependencies[0],m_scratchMemory); + if (!result) + return result; + +// printf("numAllocas = %d\n",numAllocas); + for (int i=0;i<n;i++) + { + volatile btScalar xx = m_x[i]; + if (xx != m_x[i]) + return false; + if (x[i] >= m_acceptableUpperLimitSolution) + { + return false; + } + + if (x[i] <= -m_acceptableUpperLimitSolution) + { + return false; + } + } + + for (int i=0;i<n;i++) + { + x[i] = m_x[i]; + } + + } + + return result; + } +}; + +#endif //BT_DANTZIG_SOLVER_H diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.cpp b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.cpp new file mode 100644 index 0000000000..1f4015c7c7 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.cpp @@ -0,0 +1,371 @@ +/* Copyright (C) 2004-2013 MBSim Development Team + +Code was converted for the Bullet Continuous Collision Detection and Physics Library + +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. +*/ + +//The original version is here +//https://code.google.com/p/mbsim-env/source/browse/trunk/kernel/mbsim/numerics/linear_complementarity_problem/lemke_algorithm.cc +//This file is re-distributed under the ZLib license, with permission of the original author +//Math library was replaced from fmatvec to a the file src/LinearMath/btMatrixX.h +//STL/std::vector replaced by btAlignedObjectArray + + + +#include "btLemkeAlgorithm.h" + +#undef BT_DEBUG_OSTREAM +#ifdef BT_DEBUG_OSTREAM +using namespace std; +#endif //BT_DEBUG_OSTREAM + +btScalar btMachEps() +{ + static bool calculated=false; + static btScalar machEps = btScalar(1.); + if (!calculated) + { + do { + machEps /= btScalar(2.0); + // If next epsilon yields 1, then break, because current + // epsilon is the machine epsilon. + } + while ((btScalar)(1.0 + (machEps/btScalar(2.0))) != btScalar(1.0)); +// printf( "\nCalculated Machine epsilon: %G\n", machEps ); + calculated=true; + } + return machEps; +} + +btScalar btEpsRoot() { + + static btScalar epsroot = 0.; + static bool alreadyCalculated = false; + + if (!alreadyCalculated) { + epsroot = btSqrt(btMachEps()); + alreadyCalculated = true; + } + return epsroot; +} + + + + btVectorXu btLemkeAlgorithm::solve(unsigned int maxloops /* = 0*/) +{ + + + steps = 0; + + int dim = m_q.size(); +#ifdef BT_DEBUG_OSTREAM + if(DEBUGLEVEL >= 1) { + cout << "Dimension = " << dim << endl; + } +#endif //BT_DEBUG_OSTREAM + + btVectorXu solutionVector(2 * dim); + solutionVector.setZero(); + + //, INIT, 0.); + + btMatrixXu ident(dim, dim); + ident.setIdentity(); +#ifdef BT_DEBUG_OSTREAM + cout << m_M << std::endl; +#endif + + btMatrixXu mNeg = m_M.negative(); + + btMatrixXu A(dim, 2 * dim + 2); + // + A.setSubMatrix(0, 0, dim - 1, dim - 1,ident); + A.setSubMatrix(0, dim, dim - 1, 2 * dim - 1,mNeg); + A.setSubMatrix(0, 2 * dim, dim - 1, 2 * dim, -1.f); + A.setSubMatrix(0, 2 * dim + 1, dim - 1, 2 * dim + 1,m_q); + +#ifdef BT_DEBUG_OSTREAM + cout << A << std::endl; +#endif //BT_DEBUG_OSTREAM + + + // btVectorXu q_; + // q_ >> A(0, 2 * dim + 1, dim - 1, 2 * dim + 1); + + btAlignedObjectArray<int> basis; + //At first, all w-values are in the basis + for (int i = 0; i < dim; i++) + basis.push_back(i); + + int pivotRowIndex = -1; + btScalar minValue = 1e30f; + bool greaterZero = true; + for (int i=0;i<dim;i++) + { + btScalar v =A(i,2*dim+1); + if (v<minValue) + { + minValue=v; + pivotRowIndex = i; + } + if (v<0) + greaterZero = false; + } + + + + // int pivotRowIndex = q_.minIndex();//minIndex(q_); // first row is that with lowest q-value + int z0Row = pivotRowIndex; // remember the col of z0 for ending algorithm afterwards + int pivotColIndex = 2 * dim; // first col is that of z0 + +#ifdef BT_DEBUG_OSTREAM + if (DEBUGLEVEL >= 3) + { + // cout << "A: " << A << endl; + cout << "pivotRowIndex " << pivotRowIndex << endl; + cout << "pivotColIndex " << pivotColIndex << endl; + cout << "Basis: "; + for (int i = 0; i < basis.size(); i++) + cout << basis[i] << " "; + cout << endl; + } +#endif //BT_DEBUG_OSTREAM + + if (!greaterZero) + { + + if (maxloops == 0) { + maxloops = 100; +// maxloops = UINT_MAX; //TODO: not a really nice way, problem is: maxloops should be 2^dim (=1<<dim), but this could exceed UINT_MAX and thus the result would be 0 and therefore the lemke algorithm wouldn't start but probably would find a solution within less then UINT_MAX steps. Therefore this constant is used as a upper border right now... + } + + /*start looping*/ + for(steps = 0; steps < maxloops; steps++) { + + GaussJordanEliminationStep(A, pivotRowIndex, pivotColIndex, basis); +#ifdef BT_DEBUG_OSTREAM + if (DEBUGLEVEL >= 3) { + // cout << "A: " << A << endl; + cout << "pivotRowIndex " << pivotRowIndex << endl; + cout << "pivotColIndex " << pivotColIndex << endl; + cout << "Basis: "; + for (int i = 0; i < basis.size(); i++) + cout << basis[i] << " "; + cout << endl; + } +#endif //BT_DEBUG_OSTREAM + + int pivotColIndexOld = pivotColIndex; + + /*find new column index */ + if (basis[pivotRowIndex] < dim) //if a w-value left the basis get in the correspondent z-value + pivotColIndex = basis[pivotRowIndex] + dim; + else + //else do it the other way round and get in the corresponding w-value + pivotColIndex = basis[pivotRowIndex] - dim; + + /*the column becomes part of the basis*/ + basis[pivotRowIndex] = pivotColIndexOld; + + pivotRowIndex = findLexicographicMinimum(A, pivotColIndex); + + if(z0Row == pivotRowIndex) { //if z0 leaves the basis the solution is found --> one last elimination step is necessary + GaussJordanEliminationStep(A, pivotRowIndex, pivotColIndex, basis); + basis[pivotRowIndex] = pivotColIndex; //update basis + break; + } + + } +#ifdef BT_DEBUG_OSTREAM + if(DEBUGLEVEL >= 1) { + cout << "Number of loops: " << steps << endl; + cout << "Number of maximal loops: " << maxloops << endl; + } +#endif //BT_DEBUG_OSTREAM + + if(!validBasis(basis)) { + info = -1; +#ifdef BT_DEBUG_OSTREAM + if(DEBUGLEVEL >= 1) + cerr << "Lemke-Algorithm ended with Ray-Termination (no valid solution)." << endl; +#endif //BT_DEBUG_OSTREAM + + return solutionVector; + } + + } +#ifdef BT_DEBUG_OSTREAM + if (DEBUGLEVEL >= 2) { + // cout << "A: " << A << endl; + cout << "pivotRowIndex " << pivotRowIndex << endl; + cout << "pivotColIndex " << pivotColIndex << endl; + } +#endif //BT_DEBUG_OSTREAM + + for (int i = 0; i < basis.size(); i++) + { + solutionVector[basis[i]] = A(i,2*dim+1);//q_[i]; + } + + info = 0; + + return solutionVector; + } + + int btLemkeAlgorithm::findLexicographicMinimum(const btMatrixXu& A, const int & pivotColIndex) { + int RowIndex = 0; + int dim = A.rows(); + btAlignedObjectArray<btVectorXu> Rows; + for (int row = 0; row < dim; row++) + { + + btVectorXu vec(dim + 1); + vec.setZero();//, INIT, 0.) + Rows.push_back(vec); + btScalar a = A(row, pivotColIndex); + if (a > 0) { + Rows[row][0] = A(row, 2 * dim + 1) / a; + Rows[row][1] = A(row, 2 * dim) / a; + for (int j = 2; j < dim + 1; j++) + Rows[row][j] = A(row, j - 1) / a; + +#ifdef BT_DEBUG_OSTREAM + // if (DEBUGLEVEL) { + // cout << "Rows(" << row << ") = " << Rows[row] << endl; + // } +#endif + } + } + + for (int i = 0; i < Rows.size(); i++) + { + if (Rows[i].nrm2() > 0.) { + + int j = 0; + for (; j < Rows.size(); j++) + { + if(i != j) + { + if(Rows[j].nrm2() > 0.) + { + btVectorXu test(dim + 1); + for (int ii=0;ii<dim+1;ii++) + { + test[ii] = Rows[j][ii] - Rows[i][ii]; + } + + //=Rows[j] - Rows[i] + if (! LexicographicPositive(test)) + break; + } + } + } + + if (j == Rows.size()) + { + RowIndex += i; + break; + } + } + } + + return RowIndex; + } + + bool btLemkeAlgorithm::LexicographicPositive(const btVectorXu & v) +{ + int i = 0; + // if (DEBUGLEVEL) + // cout << "v " << v << endl; + + while(i < v.size()-1 && fabs(v[i]) < btMachEps()) + i++; + if (v[i] > 0) + return true; + + return false; + } + +void btLemkeAlgorithm::GaussJordanEliminationStep(btMatrixXu& A, int pivotRowIndex, int pivotColumnIndex, const btAlignedObjectArray<int>& basis) +{ + + btScalar a = -1 / A(pivotRowIndex, pivotColumnIndex); +#ifdef BT_DEBUG_OSTREAM + cout << A << std::endl; +#endif + + for (int i = 0; i < A.rows(); i++) + { + if (i != pivotRowIndex) + { + for (int j = 0; j < A.cols(); j++) + { + if (j != pivotColumnIndex) + { + btScalar v = A(i, j); + v += A(pivotRowIndex, j) * A(i, pivotColumnIndex) * a; + A.setElem(i, j, v); + } + } + } + } + +#ifdef BT_DEBUG_OSTREAM + cout << A << std::endl; +#endif //BT_DEBUG_OSTREAM + for (int i = 0; i < A.cols(); i++) + { + A.mulElem(pivotRowIndex, i,-a); + } +#ifdef BT_DEBUG_OSTREAM + cout << A << std::endl; +#endif //#ifdef BT_DEBUG_OSTREAM + + for (int i = 0; i < A.rows(); i++) + { + if (i != pivotRowIndex) + { + A.setElem(i, pivotColumnIndex,0); + } + } +#ifdef BT_DEBUG_OSTREAM + cout << A << std::endl; +#endif //#ifdef BT_DEBUG_OSTREAM + } + + bool btLemkeAlgorithm::greaterZero(const btVectorXu & vector) +{ + bool isGreater = true; + for (int i = 0; i < vector.size(); i++) { + if (vector[i] < 0) { + isGreater = false; + break; + } + } + + return isGreater; + } + + bool btLemkeAlgorithm::validBasis(const btAlignedObjectArray<int>& basis) + { + bool isValid = true; + for (int i = 0; i < basis.size(); i++) { + if (basis[i] >= basis.size() * 2) { //then z0 is in the base + isValid = false; + break; + } + } + + return isValid; + } + + diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.h new file mode 100644 index 0000000000..7555cd9d20 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeAlgorithm.h @@ -0,0 +1,108 @@ +/* Copyright (C) 2004-2013 MBSim Development Team + +Code was converted for the Bullet Continuous Collision Detection and Physics Library + +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. +*/ + +//The original version is here +//https://code.google.com/p/mbsim-env/source/browse/trunk/kernel/mbsim/numerics/linear_complementarity_problem/lemke_algorithm.cc +//This file is re-distributed under the ZLib license, with permission of the original author (Kilian Grundl) +//Math library was replaced from fmatvec to a the file src/LinearMath/btMatrixX.h +//STL/std::vector replaced by btAlignedObjectArray + + + +#ifndef BT_NUMERICS_LEMKE_ALGORITHM_H_ +#define BT_NUMERICS_LEMKE_ALGORITHM_H_ + +#include "LinearMath/btMatrixX.h" + + +#include <vector> //todo: replace by btAlignedObjectArray + +class btLemkeAlgorithm +{ +public: + + + btLemkeAlgorithm(const btMatrixXu& M_, const btVectorXu& q_, const int & DEBUGLEVEL_ = 0) : + DEBUGLEVEL(DEBUGLEVEL_) + { + setSystem(M_, q_); + } + + /* GETTER / SETTER */ + /** + * \brief return info of solution process + */ + int getInfo() { + return info; + } + + /** + * \brief get the number of steps until the solution was found + */ + int getSteps(void) { + return steps; + } + + + + /** + * \brief set system with Matrix M and vector q + */ + void setSystem(const btMatrixXu & M_, const btVectorXu & q_) + { + m_M = M_; + m_q = q_; + } + /***************************************************/ + + /** + * \brief solve algorithm adapted from : Fast Implementation of Lemke’s Algorithm for Rigid Body Contact Simulation (John E. Lloyd) + */ + btVectorXu solve(unsigned int maxloops = 0); + + virtual ~btLemkeAlgorithm() { + } + +protected: + int findLexicographicMinimum(const btMatrixXu &A, const int & pivotColIndex); + bool LexicographicPositive(const btVectorXu & v); + void GaussJordanEliminationStep(btMatrixXu &A, int pivotRowIndex, int pivotColumnIndex, const btAlignedObjectArray<int>& basis); + bool greaterZero(const btVectorXu & vector); + bool validBasis(const btAlignedObjectArray<int>& basis); + + btMatrixXu m_M; + btVectorXu m_q; + + /** + * \brief number of steps until the Lemke algorithm found a solution + */ + unsigned int steps; + + /** + * \brief define level of debug output + */ + int DEBUGLEVEL; + + /** + * \brief did the algorithm find a solution + * + * -1 : not successful + * 0 : successful + */ + int info; +}; + + +#endif /* BT_NUMERICS_LEMKE_ALGORITHM_H_ */ diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeSolver.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeSolver.h new file mode 100644 index 0000000000..98484c3796 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btLemkeSolver.h @@ -0,0 +1,350 @@ +/* +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_LEMKE_SOLVER_H +#define BT_LEMKE_SOLVER_H + + +#include "btMLCPSolverInterface.h" +#include "btLemkeAlgorithm.h" + + + + +///The btLemkeSolver is based on "Fast Implementation of Lemke’s Algorithm for Rigid Body Contact Simulation (John E. Lloyd) " +///It is a slower but more accurate solver. Increase the m_maxLoops for better convergence, at the cost of more CPU time. +///The original implementation of the btLemkeAlgorithm was done by Kilian Grundl from the MBSim team +class btLemkeSolver : public btMLCPSolverInterface +{ +protected: + +public: + + btScalar m_maxValue; + int m_debugLevel; + int m_maxLoops; + bool m_useLoHighBounds; + + + + btLemkeSolver() + :m_maxValue(100000), + m_debugLevel(0), + m_maxLoops(1000), + m_useLoHighBounds(true) + { + } + 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 (m_useLoHighBounds) + { + + BT_PROFILE("btLemkeSolver::solveMLCP"); + int n = A.rows(); + if (0==n) + return true; + + bool fail = false; + + btVectorXu solution(n); + btVectorXu q1; + q1.resize(n); + for (int row=0;row<n;row++) + { + q1[row] = -b[row]; + } + + // cout << "A" << endl; + // cout << A << endl; + + ///////////////////////////////////// + + //slow matrix inversion, replace with LU decomposition + btMatrixXu A1; + btMatrixXu B(n,n); + { + BT_PROFILE("inverse(slow)"); + A1.resize(A.rows(),A.cols()); + for (int row=0;row<A.rows();row++) + { + for (int col=0;col<A.cols();col++) + { + A1.setElem(row,col,A(row,col)); + } + } + + btMatrixXu matrix; + matrix.resize(n,2*n); + for (int row=0;row<n;row++) + { + for (int col=0;col<n;col++) + { + matrix.setElem(row,col,A1(row,col)); + } + } + + + btScalar ratio,a; + int i,j,k; + for(i = 0; i < n; i++){ + for(j = n; j < 2*n; j++){ + if(i==(j-n)) + matrix.setElem(i,j,1.0); + else + matrix.setElem(i,j,0.0); + } + } + for(i = 0; i < n; i++){ + for(j = 0; j < n; j++){ + if(i!=j) + { + btScalar v = matrix(i,i); + if (btFuzzyZero(v)) + { + a = 0.000001f; + } + ratio = matrix(j,i)/matrix(i,i); + for(k = 0; k < 2*n; k++){ + matrix.addElem(j,k,- ratio * matrix(i,k)); + } + } + } + } + for(i = 0; i < n; i++){ + a = matrix(i,i); + if (btFuzzyZero(a)) + { + a = 0.000001f; + } + btScalar invA = 1.f/a; + for(j = 0; j < 2*n; j++){ + matrix.mulElem(i,j,invA); + } + } + + + + + + for (int row=0;row<n;row++) + { + for (int col=0;col<n;col++) + { + B.setElem(row,col,matrix(row,n+col)); + } + } + } + + btMatrixXu b1(n,1); + + btMatrixXu M(n*2,n*2); + for (int row=0;row<n;row++) + { + b1.setElem(row,0,-b[row]); + for (int col=0;col<n;col++) + { + btScalar v =B(row,col); + M.setElem(row,col,v); + M.setElem(n+row,n+col,v); + M.setElem(n+row,col,-v); + M.setElem(row,n+col,-v); + + } + } + + btMatrixXu Bb1 = B*b1; +// q = [ (-B*b1 - lo)' (hi + B*b1)' ]' + + btVectorXu qq; + qq.resize(n*2); + for (int row=0;row<n;row++) + { + qq[row] = -Bb1(row,0)-lo[row]; + qq[n+row] = Bb1(row,0)+hi[row]; + } + + btVectorXu z1; + + btMatrixXu y1; + y1.resize(n,1); + btLemkeAlgorithm lemke(M,qq,m_debugLevel); + { + BT_PROFILE("lemke.solve"); + lemke.setSystem(M,qq); + z1 = lemke.solve(m_maxLoops); + } + for (int row=0;row<n;row++) + { + y1.setElem(row,0,z1[2*n+row]-z1[3*n+row]); + } + btMatrixXu y1_b1(n,1); + for (int i=0;i<n;i++) + { + y1_b1.setElem(i,0,y1(i,0)-b1(i,0)); + } + + btMatrixXu x1; + + x1 = B*(y1_b1); + + for (int row=0;row<n;row++) + { + solution[row] = x1(row,0);//n]; + } + + int errorIndexMax = -1; + int errorIndexMin = -1; + float errorValueMax = -1e30; + float errorValueMin = 1e30; + + for (int i=0;i<n;i++) + { + x[i] = solution[i]; + volatile btScalar check = x[i]; + if (x[i] != check) + { + //printf("Lemke result is #NAN\n"); + x.setZero(); + return false; + } + + //this is some hack/safety mechanism, to discard invalid solutions from the Lemke solver + //we need to figure out why it happens, and fix it, or detect it properly) + if (x[i]>m_maxValue) + { + if (x[i]> errorValueMax) + { + fail = true; + errorIndexMax = i; + errorValueMax = x[i]; + } + ////printf("x[i] = %f,",x[i]); + } + if (x[i]<-m_maxValue) + { + if (x[i]<errorValueMin) + { + errorIndexMin = i; + errorValueMin = x[i]; + fail = true; + //printf("x[i] = %f,",x[i]); + } + } + } + if (fail) + { + int m_errorCountTimes = 0; + if (errorIndexMin<0) + errorValueMin = 0.f; + if (errorIndexMax<0) + errorValueMax = 0.f; + m_errorCountTimes++; + // printf("Error (x[%d] = %f, x[%d] = %f), resetting %d times\n", errorIndexMin,errorValueMin, errorIndexMax, errorValueMax, errorCountTimes++); + for (int i=0;i<n;i++) + { + x[i]=0.f; + } + } + return !fail; + } else + + { + int dimension = A.rows(); + if (0==dimension) + return true; + +// printf("================ solving using Lemke/Newton/Fixpoint\n"); + + btVectorXu q; + q.resize(dimension); + for (int row=0;row<dimension;row++) + { + q[row] = -b[row]; + } + + btLemkeAlgorithm lemke(A,q,m_debugLevel); + + + lemke.setSystem(A,q); + + btVectorXu solution = lemke.solve(m_maxLoops); + + //check solution + + bool fail = false; + int errorIndexMax = -1; + int errorIndexMin = -1; + float errorValueMax = -1e30; + float errorValueMin = 1e30; + + for (int i=0;i<dimension;i++) + { + x[i] = solution[i+dimension]; + volatile btScalar check = x[i]; + if (x[i] != check) + { + x.setZero(); + return false; + } + + //this is some hack/safety mechanism, to discard invalid solutions from the Lemke solver + //we need to figure out why it happens, and fix it, or detect it properly) + if (x[i]>m_maxValue) + { + if (x[i]> errorValueMax) + { + fail = true; + errorIndexMax = i; + errorValueMax = x[i]; + } + ////printf("x[i] = %f,",x[i]); + } + if (x[i]<-m_maxValue) + { + if (x[i]<errorValueMin) + { + errorIndexMin = i; + errorValueMin = x[i]; + fail = true; + //printf("x[i] = %f,",x[i]); + } + } + } + if (fail) + { + static int errorCountTimes = 0; + if (errorIndexMin<0) + errorValueMin = 0.f; + if (errorIndexMax<0) + errorValueMax = 0.f; + printf("Error (x[%d] = %f, x[%d] = %f), resetting %d times\n", errorIndexMin,errorValueMin, errorIndexMax, errorValueMax, errorCountTimes++); + for (int i=0;i<dimension;i++) + { + x[i]=0.f; + } + } + + + return !fail; + } + return true; + + } + +}; + +#endif //BT_LEMKE_SOLVER_H diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.cpp b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.cpp new file mode 100644 index 0000000000..8f54c52626 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.cpp @@ -0,0 +1,639 @@ +/* +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 + +#include "btMLCPSolver.h" +#include "LinearMath/btMatrixX.h" +#include "LinearMath/btQuickprof.h" +#include "btSolveProjectedGaussSeidel.h" + + +btMLCPSolver::btMLCPSolver( btMLCPSolverInterface* solver) +:m_solver(solver), +m_fallback(0) +{ +} + +btMLCPSolver::~btMLCPSolver() +{ +} + +bool gUseMatrixMultiply = false; +bool interleaveContactAndFriction = false; + +btScalar btMLCPSolver::solveGroupCacheFriendlySetup(btCollisionObject** bodies, int numBodiesUnUsed, btPersistentManifold** manifoldPtr, int numManifolds,btTypedConstraint** constraints,int numConstraints,const btContactSolverInfo& infoGlobal,btIDebugDraw* debugDrawer) +{ + btSequentialImpulseConstraintSolver::solveGroupCacheFriendlySetup( bodies, numBodiesUnUsed, manifoldPtr, numManifolds,constraints,numConstraints,infoGlobal,debugDrawer); + + { + BT_PROFILE("gather constraint data"); + + int numFrictionPerContact = m_tmpSolverContactConstraintPool.size()==m_tmpSolverContactFrictionConstraintPool.size()? 1 : 2; + + + // int numBodies = m_tmpSolverBodyPool.size(); + m_allConstraintPtrArray.resize(0); + m_limitDependencies.resize(m_tmpSolverNonContactConstraintPool.size()+m_tmpSolverContactConstraintPool.size()+m_tmpSolverContactFrictionConstraintPool.size()); + btAssert(m_limitDependencies.size() == m_tmpSolverNonContactConstraintPool.size()+m_tmpSolverContactConstraintPool.size()+m_tmpSolverContactFrictionConstraintPool.size()); + // printf("m_limitDependencies.size() = %d\n",m_limitDependencies.size()); + + int dindex = 0; + for (int i=0;i<m_tmpSolverNonContactConstraintPool.size();i++) + { + m_allConstraintPtrArray.push_back(&m_tmpSolverNonContactConstraintPool[i]); + m_limitDependencies[dindex++] = -1; + } + + ///The btSequentialImpulseConstraintSolver moves all friction constraints at the very end, we can also interleave them instead + + int firstContactConstraintOffset=dindex; + + if (interleaveContactAndFriction) + { + for (int i=0;i<m_tmpSolverContactConstraintPool.size();i++) + { + m_allConstraintPtrArray.push_back(&m_tmpSolverContactConstraintPool[i]); + m_limitDependencies[dindex++] = -1; + m_allConstraintPtrArray.push_back(&m_tmpSolverContactFrictionConstraintPool[i*numFrictionPerContact]); + int findex = (m_tmpSolverContactFrictionConstraintPool[i*numFrictionPerContact].m_frictionIndex*(1+numFrictionPerContact)); + m_limitDependencies[dindex++] = findex +firstContactConstraintOffset; + if (numFrictionPerContact==2) + { + m_allConstraintPtrArray.push_back(&m_tmpSolverContactFrictionConstraintPool[i*numFrictionPerContact+1]); + m_limitDependencies[dindex++] = findex+firstContactConstraintOffset; + } + } + } else + { + for (int i=0;i<m_tmpSolverContactConstraintPool.size();i++) + { + m_allConstraintPtrArray.push_back(&m_tmpSolverContactConstraintPool[i]); + m_limitDependencies[dindex++] = -1; + } + for (int i=0;i<m_tmpSolverContactFrictionConstraintPool.size();i++) + { + m_allConstraintPtrArray.push_back(&m_tmpSolverContactFrictionConstraintPool[i]); + m_limitDependencies[dindex++] = m_tmpSolverContactFrictionConstraintPool[i].m_frictionIndex+firstContactConstraintOffset; + } + + } + + + if (!m_allConstraintPtrArray.size()) + { + m_A.resize(0,0); + m_b.resize(0); + m_x.resize(0); + m_lo.resize(0); + m_hi.resize(0); + return 0.f; + } + } + + + if (gUseMatrixMultiply) + { + BT_PROFILE("createMLCP"); + createMLCP(infoGlobal); + } + else + { + BT_PROFILE("createMLCPFast"); + createMLCPFast(infoGlobal); + } + + return 0.f; +} + +bool btMLCPSolver::solveMLCP(const btContactSolverInfo& infoGlobal) +{ + bool result = true; + + if (m_A.rows()==0) + return true; + + //if using split impulse, we solve 2 separate (M)LCPs + if (infoGlobal.m_splitImpulse) + { + btMatrixXu Acopy = m_A; + btAlignedObjectArray<int> limitDependenciesCopy = m_limitDependencies; +// printf("solve first LCP\n"); + result = m_solver->solveMLCP(m_A, m_b, m_x, m_lo,m_hi, m_limitDependencies,infoGlobal.m_numIterations ); + if (result) + result = m_solver->solveMLCP(Acopy, m_bSplit, m_xSplit, m_lo,m_hi, limitDependenciesCopy,infoGlobal.m_numIterations ); + + } else + { + result = m_solver->solveMLCP(m_A, m_b, m_x, m_lo,m_hi, m_limitDependencies,infoGlobal.m_numIterations ); + } + return result; +} + +struct btJointNode +{ + int jointIndex; // pointer to enclosing dxJoint object + int otherBodyIndex; // *other* body this joint is connected to + int nextJointNodeIndex;//-1 for null + int constraintRowIndex; +}; + + + +void btMLCPSolver::createMLCPFast(const btContactSolverInfo& infoGlobal) +{ + int numContactRows = interleaveContactAndFriction ? 3 : 1; + + int numConstraintRows = m_allConstraintPtrArray.size(); + int n = numConstraintRows; + { + BT_PROFILE("init b (rhs)"); + m_b.resize(numConstraintRows); + m_bSplit.resize(numConstraintRows); + m_b.setZero(); + m_bSplit.setZero(); + for (int i=0;i<numConstraintRows ;i++) + { + btScalar jacDiag = m_allConstraintPtrArray[i]->m_jacDiagABInv; + if (!btFuzzyZero(jacDiag)) + { + btScalar rhs = m_allConstraintPtrArray[i]->m_rhs; + btScalar rhsPenetration = m_allConstraintPtrArray[i]->m_rhsPenetration; + m_b[i]=rhs/jacDiag; + m_bSplit[i] = rhsPenetration/jacDiag; + } + + } + } + +// btScalar* w = 0; +// int nub = 0; + + m_lo.resize(numConstraintRows); + m_hi.resize(numConstraintRows); + + { + BT_PROFILE("init lo/ho"); + + for (int i=0;i<numConstraintRows;i++) + { + if (0)//m_limitDependencies[i]>=0) + { + m_lo[i] = -BT_INFINITY; + m_hi[i] = BT_INFINITY; + } else + { + m_lo[i] = m_allConstraintPtrArray[i]->m_lowerLimit; + m_hi[i] = m_allConstraintPtrArray[i]->m_upperLimit; + } + } + } + + // + int m=m_allConstraintPtrArray.size(); + + int numBodies = m_tmpSolverBodyPool.size(); + btAlignedObjectArray<int> bodyJointNodeArray; + { + BT_PROFILE("bodyJointNodeArray.resize"); + bodyJointNodeArray.resize(numBodies,-1); + } + btAlignedObjectArray<btJointNode> jointNodeArray; + { + BT_PROFILE("jointNodeArray.reserve"); + jointNodeArray.reserve(2*m_allConstraintPtrArray.size()); + } + + btMatrixXu& J3 = m_scratchJ3; + { + BT_PROFILE("J3.resize"); + J3.resize(2*m,8); + } + btMatrixXu& JinvM3 = m_scratchJInvM3; + { + BT_PROFILE("JinvM3.resize/setZero"); + + JinvM3.resize(2*m,8); + JinvM3.setZero(); + J3.setZero(); + } + int cur=0; + int rowOffset = 0; + btAlignedObjectArray<int>& ofs = m_scratchOfs; + { + BT_PROFILE("ofs resize"); + ofs.resize(0); + ofs.resizeNoInitialize(m_allConstraintPtrArray.size()); + } + { + BT_PROFILE("Compute J and JinvM"); + int c=0; + + int numRows = 0; + + for (int i=0;i<m_allConstraintPtrArray.size();i+=numRows,c++) + { + ofs[c] = rowOffset; + int sbA = m_allConstraintPtrArray[i]->m_solverBodyIdA; + int sbB = m_allConstraintPtrArray[i]->m_solverBodyIdB; + btRigidBody* orgBodyA = m_tmpSolverBodyPool[sbA].m_originalBody; + btRigidBody* orgBodyB = m_tmpSolverBodyPool[sbB].m_originalBody; + + numRows = i<m_tmpSolverNonContactConstraintPool.size() ? m_tmpConstraintSizesPool[c].m_numConstraintRows : numContactRows ; + if (orgBodyA) + { + { + int slotA=-1; + //find free jointNode slot for sbA + slotA =jointNodeArray.size(); + jointNodeArray.expand();//NonInitializing(); + int prevSlot = bodyJointNodeArray[sbA]; + bodyJointNodeArray[sbA] = slotA; + jointNodeArray[slotA].nextJointNodeIndex = prevSlot; + jointNodeArray[slotA].jointIndex = c; + jointNodeArray[slotA].constraintRowIndex = i; + jointNodeArray[slotA].otherBodyIndex = orgBodyB ? sbB : -1; + } + for (int row=0;row<numRows;row++,cur++) + { + btVector3 normalInvMass = m_allConstraintPtrArray[i+row]->m_contactNormal1 * orgBodyA->getInvMass(); + btVector3 relPosCrossNormalInvInertia = m_allConstraintPtrArray[i+row]->m_relpos1CrossNormal * orgBodyA->getInvInertiaTensorWorld(); + + for (int r=0;r<3;r++) + { + J3.setElem(cur,r,m_allConstraintPtrArray[i+row]->m_contactNormal1[r]); + J3.setElem(cur,r+4,m_allConstraintPtrArray[i+row]->m_relpos1CrossNormal[r]); + JinvM3.setElem(cur,r,normalInvMass[r]); + JinvM3.setElem(cur,r+4,relPosCrossNormalInvInertia[r]); + } + J3.setElem(cur,3,0); + JinvM3.setElem(cur,3,0); + J3.setElem(cur,7,0); + JinvM3.setElem(cur,7,0); + } + } else + { + cur += numRows; + } + if (orgBodyB) + { + + { + int slotB=-1; + //find free jointNode slot for sbA + slotB =jointNodeArray.size(); + jointNodeArray.expand();//NonInitializing(); + int prevSlot = bodyJointNodeArray[sbB]; + bodyJointNodeArray[sbB] = slotB; + jointNodeArray[slotB].nextJointNodeIndex = prevSlot; + jointNodeArray[slotB].jointIndex = c; + jointNodeArray[slotB].otherBodyIndex = orgBodyA ? sbA : -1; + jointNodeArray[slotB].constraintRowIndex = i; + } + + for (int row=0;row<numRows;row++,cur++) + { + btVector3 normalInvMassB = m_allConstraintPtrArray[i+row]->m_contactNormal2*orgBodyB->getInvMass(); + btVector3 relPosInvInertiaB = m_allConstraintPtrArray[i+row]->m_relpos2CrossNormal * orgBodyB->getInvInertiaTensorWorld(); + + for (int r=0;r<3;r++) + { + J3.setElem(cur,r,m_allConstraintPtrArray[i+row]->m_contactNormal2[r]); + J3.setElem(cur,r+4,m_allConstraintPtrArray[i+row]->m_relpos2CrossNormal[r]); + JinvM3.setElem(cur,r,normalInvMassB[r]); + JinvM3.setElem(cur,r+4,relPosInvInertiaB[r]); + } + J3.setElem(cur,3,0); + JinvM3.setElem(cur,3,0); + J3.setElem(cur,7,0); + JinvM3.setElem(cur,7,0); + } + } + else + { + cur += numRows; + } + rowOffset+=numRows; + + } + + } + + + //compute JinvM = J*invM. + const btScalar* JinvM = JinvM3.getBufferPointer(); + + const btScalar* Jptr = J3.getBufferPointer(); + { + BT_PROFILE("m_A.resize"); + m_A.resize(n,n); + } + + { + BT_PROFILE("m_A.setZero"); + m_A.setZero(); + } + int c=0; + { + int numRows = 0; + BT_PROFILE("Compute A"); + for (int i=0;i<m_allConstraintPtrArray.size();i+= numRows,c++) + { + int row__ = ofs[c]; + int sbA = m_allConstraintPtrArray[i]->m_solverBodyIdA; + int sbB = m_allConstraintPtrArray[i]->m_solverBodyIdB; + // btRigidBody* orgBodyA = m_tmpSolverBodyPool[sbA].m_originalBody; + // btRigidBody* orgBodyB = m_tmpSolverBodyPool[sbB].m_originalBody; + + numRows = i<m_tmpSolverNonContactConstraintPool.size() ? m_tmpConstraintSizesPool[c].m_numConstraintRows : numContactRows ; + + const btScalar *JinvMrow = JinvM + 2*8*(size_t)row__; + + { + int startJointNodeA = bodyJointNodeArray[sbA]; + while (startJointNodeA>=0) + { + int j0 = jointNodeArray[startJointNodeA].jointIndex; + int cr0 = jointNodeArray[startJointNodeA].constraintRowIndex; + if (j0<c) + { + + int numRowsOther = cr0 < m_tmpSolverNonContactConstraintPool.size() ? m_tmpConstraintSizesPool[j0].m_numConstraintRows : numContactRows; + size_t ofsother = (m_allConstraintPtrArray[cr0]->m_solverBodyIdB == sbA) ? 8*numRowsOther : 0; + //printf("%d joint i %d and j0: %d: ",count++,i,j0); + m_A.multiplyAdd2_p8r ( JinvMrow, + Jptr + 2*8*(size_t)ofs[j0] + ofsother, numRows, numRowsOther, row__,ofs[j0]); + } + startJointNodeA = jointNodeArray[startJointNodeA].nextJointNodeIndex; + } + } + + { + int startJointNodeB = bodyJointNodeArray[sbB]; + while (startJointNodeB>=0) + { + int j1 = jointNodeArray[startJointNodeB].jointIndex; + int cj1 = jointNodeArray[startJointNodeB].constraintRowIndex; + + if (j1<c) + { + int numRowsOther = cj1 < m_tmpSolverNonContactConstraintPool.size() ? m_tmpConstraintSizesPool[j1].m_numConstraintRows : numContactRows; + size_t ofsother = (m_allConstraintPtrArray[cj1]->m_solverBodyIdB == sbB) ? 8*numRowsOther : 0; + m_A.multiplyAdd2_p8r ( JinvMrow + 8*(size_t)numRows, + Jptr + 2*8*(size_t)ofs[j1] + ofsother, numRows, numRowsOther, row__,ofs[j1]); + } + startJointNodeB = jointNodeArray[startJointNodeB].nextJointNodeIndex; + } + } + } + + { + BT_PROFILE("compute diagonal"); + // compute diagonal blocks of m_A + + int row__ = 0; + int numJointRows = m_allConstraintPtrArray.size(); + + int jj=0; + for (;row__<numJointRows;) + { + + //int sbA = m_allConstraintPtrArray[row__]->m_solverBodyIdA; + int sbB = m_allConstraintPtrArray[row__]->m_solverBodyIdB; + // btRigidBody* orgBodyA = m_tmpSolverBodyPool[sbA].m_originalBody; + btRigidBody* orgBodyB = m_tmpSolverBodyPool[sbB].m_originalBody; + + + const unsigned int infom = row__ < m_tmpSolverNonContactConstraintPool.size() ? m_tmpConstraintSizesPool[jj].m_numConstraintRows : numContactRows; + + const btScalar *JinvMrow = JinvM + 2*8*(size_t)row__; + const btScalar *Jrow = Jptr + 2*8*(size_t)row__; + m_A.multiply2_p8r (JinvMrow, Jrow, infom, infom, row__,row__); + if (orgBodyB) + { + m_A.multiplyAdd2_p8r (JinvMrow + 8*(size_t)infom, Jrow + 8*(size_t)infom, infom, infom, row__,row__); + } + row__ += infom; + jj++; + } + } + } + + if (1) + { + // add cfm to the diagonal of m_A + for ( int i=0; i<m_A.rows(); ++i) + { + m_A.setElem(i,i,m_A(i,i)+ infoGlobal.m_globalCfm/ infoGlobal.m_timeStep); + } + } + + ///fill the upper triangle of the matrix, to make it symmetric + { + BT_PROFILE("fill the upper triangle "); + m_A.copyLowerToUpperTriangle(); + } + + { + BT_PROFILE("resize/init x"); + m_x.resize(numConstraintRows); + m_xSplit.resize(numConstraintRows); + + if (infoGlobal.m_solverMode&SOLVER_USE_WARMSTARTING) + { + for (int i=0;i<m_allConstraintPtrArray.size();i++) + { + const btSolverConstraint& c = *m_allConstraintPtrArray[i]; + m_x[i]=c.m_appliedImpulse; + m_xSplit[i] = c.m_appliedPushImpulse; + } + } else + { + m_x.setZero(); + m_xSplit.setZero(); + } + } + +} + +void btMLCPSolver::createMLCP(const btContactSolverInfo& infoGlobal) +{ + int numBodies = this->m_tmpSolverBodyPool.size(); + int numConstraintRows = m_allConstraintPtrArray.size(); + + m_b.resize(numConstraintRows); + if (infoGlobal.m_splitImpulse) + m_bSplit.resize(numConstraintRows); + + m_bSplit.setZero(); + m_b.setZero(); + + for (int i=0;i<numConstraintRows ;i++) + { + if (m_allConstraintPtrArray[i]->m_jacDiagABInv) + { + m_b[i]=m_allConstraintPtrArray[i]->m_rhs/m_allConstraintPtrArray[i]->m_jacDiagABInv; + if (infoGlobal.m_splitImpulse) + m_bSplit[i] = m_allConstraintPtrArray[i]->m_rhsPenetration/m_allConstraintPtrArray[i]->m_jacDiagABInv; + } + } + + btMatrixXu& Minv = m_scratchMInv; + Minv.resize(6*numBodies,6*numBodies); + Minv.setZero(); + for (int i=0;i<numBodies;i++) + { + const btSolverBody& rb = m_tmpSolverBodyPool[i]; + const btVector3& invMass = rb.m_invMass; + setElem(Minv,i*6+0,i*6+0,invMass[0]); + setElem(Minv,i*6+1,i*6+1,invMass[1]); + setElem(Minv,i*6+2,i*6+2,invMass[2]); + btRigidBody* orgBody = m_tmpSolverBodyPool[i].m_originalBody; + + for (int r=0;r<3;r++) + for (int c=0;c<3;c++) + setElem(Minv,i*6+3+r,i*6+3+c,orgBody? orgBody->getInvInertiaTensorWorld()[r][c] : 0); + } + + btMatrixXu& J = m_scratchJ; + J.resize(numConstraintRows,6*numBodies); + J.setZero(); + + m_lo.resize(numConstraintRows); + m_hi.resize(numConstraintRows); + + for (int i=0;i<numConstraintRows;i++) + { + + m_lo[i] = m_allConstraintPtrArray[i]->m_lowerLimit; + m_hi[i] = m_allConstraintPtrArray[i]->m_upperLimit; + + int bodyIndex0 = m_allConstraintPtrArray[i]->m_solverBodyIdA; + int bodyIndex1 = m_allConstraintPtrArray[i]->m_solverBodyIdB; + if (m_tmpSolverBodyPool[bodyIndex0].m_originalBody) + { + setElem(J,i,6*bodyIndex0+0,m_allConstraintPtrArray[i]->m_contactNormal1[0]); + setElem(J,i,6*bodyIndex0+1,m_allConstraintPtrArray[i]->m_contactNormal1[1]); + setElem(J,i,6*bodyIndex0+2,m_allConstraintPtrArray[i]->m_contactNormal1[2]); + setElem(J,i,6*bodyIndex0+3,m_allConstraintPtrArray[i]->m_relpos1CrossNormal[0]); + setElem(J,i,6*bodyIndex0+4,m_allConstraintPtrArray[i]->m_relpos1CrossNormal[1]); + setElem(J,i,6*bodyIndex0+5,m_allConstraintPtrArray[i]->m_relpos1CrossNormal[2]); + } + if (m_tmpSolverBodyPool[bodyIndex1].m_originalBody) + { + setElem(J,i,6*bodyIndex1+0,m_allConstraintPtrArray[i]->m_contactNormal2[0]); + setElem(J,i,6*bodyIndex1+1,m_allConstraintPtrArray[i]->m_contactNormal2[1]); + setElem(J,i,6*bodyIndex1+2,m_allConstraintPtrArray[i]->m_contactNormal2[2]); + setElem(J,i,6*bodyIndex1+3,m_allConstraintPtrArray[i]->m_relpos2CrossNormal[0]); + setElem(J,i,6*bodyIndex1+4,m_allConstraintPtrArray[i]->m_relpos2CrossNormal[1]); + setElem(J,i,6*bodyIndex1+5,m_allConstraintPtrArray[i]->m_relpos2CrossNormal[2]); + } + } + + btMatrixXu& J_transpose = m_scratchJTranspose; + J_transpose= J.transpose(); + + btMatrixXu& tmp = m_scratchTmp; + + { + { + BT_PROFILE("J*Minv"); + tmp = J*Minv; + + } + { + BT_PROFILE("J*tmp"); + m_A = tmp*J_transpose; + } + } + + if (1) + { + // add cfm to the diagonal of m_A + for ( int i=0; i<m_A.rows(); ++i) + { + m_A.setElem(i,i,m_A(i,i)+ infoGlobal.m_globalCfm / infoGlobal.m_timeStep); + } + } + + m_x.resize(numConstraintRows); + if (infoGlobal.m_splitImpulse) + m_xSplit.resize(numConstraintRows); +// m_x.setZero(); + + for (int i=0;i<m_allConstraintPtrArray.size();i++) + { + const btSolverConstraint& c = *m_allConstraintPtrArray[i]; + m_x[i]=c.m_appliedImpulse; + if (infoGlobal.m_splitImpulse) + m_xSplit[i] = c.m_appliedPushImpulse; + } + +} + + +btScalar btMLCPSolver::solveGroupCacheFriendlyIterations(btCollisionObject** bodies ,int numBodies,btPersistentManifold** manifoldPtr, int numManifolds,btTypedConstraint** constraints,int numConstraints,const btContactSolverInfo& infoGlobal,btIDebugDraw* debugDrawer) +{ + bool result = true; + { + BT_PROFILE("solveMLCP"); +// printf("m_A(%d,%d)\n", m_A.rows(),m_A.cols()); + result = solveMLCP(infoGlobal); + } + + //check if solution is valid, and otherwise fallback to btSequentialImpulseConstraintSolver::solveGroupCacheFriendlyIterations + if (result) + { + BT_PROFILE("process MLCP results"); + for (int i=0;i<m_allConstraintPtrArray.size();i++) + { + { + btSolverConstraint& c = *m_allConstraintPtrArray[i]; + int sbA = c.m_solverBodyIdA; + int sbB = c.m_solverBodyIdB; + //btRigidBody* orgBodyA = m_tmpSolverBodyPool[sbA].m_originalBody; + // btRigidBody* orgBodyB = m_tmpSolverBodyPool[sbB].m_originalBody; + + btSolverBody& solverBodyA = m_tmpSolverBodyPool[sbA]; + btSolverBody& solverBodyB = m_tmpSolverBodyPool[sbB]; + + { + btScalar deltaImpulse = m_x[i]-c.m_appliedImpulse; + c.m_appliedImpulse = m_x[i]; + solverBodyA.internalApplyImpulse(c.m_contactNormal1*solverBodyA.internalGetInvMass(),c.m_angularComponentA,deltaImpulse); + solverBodyB.internalApplyImpulse(c.m_contactNormal2*solverBodyB.internalGetInvMass(),c.m_angularComponentB,deltaImpulse); + } + + if (infoGlobal.m_splitImpulse) + { + btScalar deltaImpulse = m_xSplit[i] - c.m_appliedPushImpulse; + solverBodyA.internalApplyPushImpulse(c.m_contactNormal1*solverBodyA.internalGetInvMass(),c.m_angularComponentA,deltaImpulse); + solverBodyB.internalApplyPushImpulse(c.m_contactNormal2*solverBodyB.internalGetInvMass(),c.m_angularComponentB,deltaImpulse); + c.m_appliedPushImpulse = m_xSplit[i]; + } + + } + } + } + else + { + // printf("m_fallback = %d\n",m_fallback); + m_fallback++; + btSequentialImpulseConstraintSolver::solveGroupCacheFriendlyIterations(bodies ,numBodies,manifoldPtr, numManifolds,constraints,numConstraints,infoGlobal,debugDrawer); + } + + return 0.f; +} + + diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.h new file mode 100644 index 0000000000..26b482ddc1 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolver.h @@ -0,0 +1,94 @@ +/* +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_MLCP_SOLVER_H +#define BT_MLCP_SOLVER_H + +#include "BulletDynamics/ConstraintSolver/btSequentialImpulseConstraintSolver.h" +#include "LinearMath/btMatrixX.h" +#include "BulletDynamics/MLCPSolvers/btMLCPSolverInterface.h" + +class btMLCPSolver : public btSequentialImpulseConstraintSolver +{ + +protected: + + btMatrixXu m_A; + btVectorXu m_b; + btVectorXu m_x; + btVectorXu m_lo; + btVectorXu m_hi; + + ///when using 'split impulse' we solve two separate (M)LCPs + btVectorXu m_bSplit; + btVectorXu m_xSplit; + btVectorXu m_bSplit1; + btVectorXu m_xSplit2; + + btAlignedObjectArray<int> m_limitDependencies; + btAlignedObjectArray<btSolverConstraint*> m_allConstraintPtrArray; + btMLCPSolverInterface* m_solver; + int m_fallback; + + /// The following scratch variables are not stateful -- contents are cleared prior to each use. + /// They are only cached here to avoid extra memory allocations and deallocations and to ensure + /// that multiple instances of the solver can be run in parallel. + btMatrixXu m_scratchJ3; + btMatrixXu m_scratchJInvM3; + btAlignedObjectArray<int> m_scratchOfs; + btMatrixXu m_scratchMInv; + btMatrixXu m_scratchJ; + btMatrixXu m_scratchJTranspose; + btMatrixXu m_scratchTmp; + + virtual btScalar solveGroupCacheFriendlySetup(btCollisionObject** bodies, int numBodies, btPersistentManifold** manifoldPtr, int numManifolds,btTypedConstraint** constraints,int numConstraints,const btContactSolverInfo& infoGlobal,btIDebugDraw* debugDrawer); + virtual btScalar solveGroupCacheFriendlyIterations(btCollisionObject** bodies ,int numBodies,btPersistentManifold** manifoldPtr, int numManifolds,btTypedConstraint** constraints,int numConstraints,const btContactSolverInfo& infoGlobal,btIDebugDraw* debugDrawer); + + + virtual void createMLCP(const btContactSolverInfo& infoGlobal); + virtual void createMLCPFast(const btContactSolverInfo& infoGlobal); + + //return true is it solves the problem successfully + virtual bool solveMLCP(const btContactSolverInfo& infoGlobal); + +public: + + btMLCPSolver( btMLCPSolverInterface* solver); + virtual ~btMLCPSolver(); + + void setMLCPSolver(btMLCPSolverInterface* solver) + { + m_solver = solver; + } + + int getNumFallbacks() const + { + return m_fallback; + } + void setNumFallbacks(int num) + { + m_fallback = num; + } + + virtual btConstraintSolverType getSolverType() const + { + return BT_MLCP_SOLVER; + } + +}; + + +#endif //BT_MLCP_SOLVER_H diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolverInterface.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolverInterface.h new file mode 100644 index 0000000000..25bb3f6d32 --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btMLCPSolverInterface.h @@ -0,0 +1,33 @@ +/* +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_MLCP_SOLVER_INTERFACE_H +#define BT_MLCP_SOLVER_INTERFACE_H + +#include "LinearMath/btMatrixX.h" + +class btMLCPSolverInterface +{ +public: + virtual ~btMLCPSolverInterface() + { + } + + //return true is it solves the problem successfully + 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)=0; +}; + +#endif //BT_MLCP_SOLVER_INTERFACE_H diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btPATHSolver.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btPATHSolver.h new file mode 100644 index 0000000000..9ec31a6d4e --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btPATHSolver.h @@ -0,0 +1,151 @@ +/* +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_PATH_SOLVER_H +#define BT_PATH_SOLVER_H + +//#define BT_USE_PATH +#ifdef BT_USE_PATH + +extern "C" { +#include "PATH/SimpleLCP.h" +#include "PATH/License.h" +#include "PATH/Error_Interface.h" +}; + void __stdcall MyError(Void *data, Char *msg) +{ + printf("Path Error: %s\n",msg); +} + void __stdcall MyWarning(Void *data, Char *msg) +{ + printf("Path Warning: %s\n",msg); +} + +Error_Interface e; + + + +#include "btMLCPSolverInterface.h" +#include "Dantzig/lcp.h" + +class btPathSolver : public btMLCPSolverInterface +{ +public: + + btPathSolver() + { + License_SetString("2069810742&Courtesy_License&&&USR&2013&14_12_2011&1000&PATH&GEN&31_12_2013&0_0_0&0&0_0"); + e.error_data = 0; + e.warning = MyWarning; + e.error = MyError; + Error_SetInterface(&e); + } + + + 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) + { + MCP_Termination status; + + + int numVariables = b.rows(); + if (0==numVariables) + return true; + + /* - variables - the number of variables in the problem + - m_nnz - the number of nonzeros in the M matrix + - m_i - a vector of size m_nnz containing the row indices for M + - m_j - a vector of size m_nnz containing the column indices for M + - m_ij - a vector of size m_nnz containing the data for M + - q - a vector of size variables + - lb - a vector of size variables containing the lower bounds on x + - ub - a vector of size variables containing the upper bounds on x + */ + btAlignedObjectArray<double> values; + btAlignedObjectArray<int> rowIndices; + btAlignedObjectArray<int> colIndices; + + for (int i=0;i<A.rows();i++) + { + for (int j=0;j<A.cols();j++) + { + if (A(i,j)!=0.f) + { + //add 1, because Path starts at 1, instead of 0 + rowIndices.push_back(i+1); + colIndices.push_back(j+1); + values.push_back(A(i,j)); + } + } + } + int numNonZero = rowIndices.size(); + btAlignedObjectArray<double> zResult; + zResult.resize(numVariables); + btAlignedObjectArray<double> rhs; + btAlignedObjectArray<double> upperBounds; + btAlignedObjectArray<double> lowerBounds; + for (int i=0;i<numVariables;i++) + { + upperBounds.push_back(hi[i]); + lowerBounds.push_back(lo[i]); + rhs.push_back(-b[i]); + } + + + SimpleLCP(numVariables,numNonZero,&rowIndices[0],&colIndices[0],&values[0],&rhs[0],&lowerBounds[0],&upperBounds[0], &status, &zResult[0]); + + if (status != MCP_Solved) + { + static const char* gReturnMsgs[] = { + "Invalid return", + "MCP_Solved: The problem was solved", + "MCP_NoProgress: A stationary point was found", + "MCP_MajorIterationLimit: Major iteration limit met", + "MCP_MinorIterationLimit: Cumulative minor iteration limit met", + "MCP_TimeLimit: Ran out of time", + "MCP_UserInterrupt: Control-C, typically", + "MCP_BoundError: Problem has a bound error", + "MCP_DomainError: Could not find starting point", + "MCP_Infeasible: Problem has no solution", + "MCP_Error: An error occurred within the code", + "MCP_LicenseError: License could not be found", + "MCP_OK" + }; + + printf("ERROR: The PATH MCP solver failed: %s\n", gReturnMsgs[(unsigned int)status]);// << std::endl; + printf("using Projected Gauss Seidel fallback\n"); + + return false; + } else + { + for (int i=0;i<numVariables;i++) + { + x[i] = zResult[i]; + //check for #NAN + if (x[i] != zResult[i]) + return false; + } + return true; + + } + + } +}; + +#endif //BT_USE_PATH + + +#endif //BT_PATH_SOLVER_H diff --git a/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btSolveProjectedGaussSeidel.h b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btSolveProjectedGaussSeidel.h new file mode 100644 index 0000000000..c0b40ffd9f --- /dev/null +++ b/thirdparty/bullet/src/BulletDynamics/MLCPSolvers/btSolveProjectedGaussSeidel.h @@ -0,0 +1,110 @@ +/* +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 |