/// -*- tab-width: 4; Mode: C++; c-basic-offset: 4; indent-tabs-mode: nil -*- /* * matrix3.cpp * Copyright (C) Siddharth Bharat Purohit, 3DRobotics Inc. 2015 * * This file is free software: you can redistribute it and/or modify it * under the terms of the GNU General Public License as published by the * Free Software Foundation, either version 3 of the License, or * (at your option) any later version. * * This file 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 GNU General Public License for more details. * * You should have received a copy of the GNU General Public License along * with this program. If not, see . */ #pragma GCC optimize("O3") #include #include #include extern const AP_HAL::HAL& hal; //TODO: use higher precision datatypes to achieve more accuracy for matrix algebra operations /* * Does matrix multiplication of two regular/square matrices * * @param A, Matrix A * @param B, Matrix B * @param n, dimemsion of square matrices * @returns multiplied matrix i.e. A*B */ float* mat_mul(float *A, float *B, uint8_t n) { float* ret = new float[n*n]; memset(ret,0.0f,n*n*sizeof(float)); for(uint8_t i = 0; i < n; i++) { for(uint8_t j = 0; j < n; j++) { for(uint8_t k = 0;k < n; k++) { ret[i*n + j] += A[i*n + k] * B[k*n + j]; } } } return ret; } static inline void swap(float &a, float &b) { float c; c = a; a = b; b = c; } /* * calculates pivot matrix such that all the larger elements in the row are on diagonal * * @param A, input matrix matrix * @param pivot * @param n, dimenstion of square matrix * @returns false = matrix is Singular or non positive definite, true = matrix inversion successful */ void mat_pivot(float* A, float* pivot, uint8_t n) { for(uint8_t i = 0;i fabsf(A[max_j*n + i])) { max_j = j; } } if(max_j != i) { for(uint8_t k = 0; k < n; k++) { swap(pivot[i*n + k], pivot[max_j*n + k]); } } } } /* * calculates matrix inverse of Lower trangular matrix using forward substitution * * @param L, lower triangular matrix * @param out, Output inverted lower triangular matrix * @param n, dimension of matrix */ void mat_forward_sub(float *L, float *out, uint8_t n) { // Forward substitution solve LY = I for(int i = 0; i < n; i++) { out[i*n + i] = 1/L[i*n + i]; for (int j = i+1; j < n; j++) { for (int k = i; k < j; k++) { out[j*n + i] -= L[j*n + k] * out[k*n + i]; } out[j*n + i] /= L[j*n + j]; } } } /* * calculates matrix inverse of Upper trangular matrix using backward substitution * * @param U, upper triangular matrix * @param out, Output inverted upper triangular matrix * @param n, dimension of matrix */ void mat_back_sub(float *U, float *out, uint8_t n) { // Backward Substitution solve UY = I for(int i = n-1; i >= 0; i--) { out[i*n + i] = 1/U[i*n + i]; for (int j = i - 1; j >= 0; j--) { for (int k = i; k > j; k--) { out[j*n + i] -= U[j*n + k] * out[k*n + i]; } out[j*n + i] /= U[j*n + j]; } } } /* * Decomposes square matrix into Lower and Upper triangular matrices such that * A*P = L*U, where P is the pivot matrix * ref: http://rosettacode.org/wiki/LU_decomposition * @param U, upper triangular matrix * @param out, Output inverted upper triangular matrix * @param n, dimension of matrix */ void mat_LU_decompose(float* A, float* L, float* U, float *P, uint8_t n) { memset(L,0,n*n*sizeof(float)); memset(U,0,n*n*sizeof(float)); memset(P,0,n*n*sizeof(float)); mat_pivot(A,P,n); float *APrime = mat_mul(P,A,n); for(uint8_t i = 0; i < n; i++) { L[i*n + i] = 1; } for(uint8_t i = 0; i < n; i++) { for(uint8_t j = 0; j < n; j++) { if(j <= i) { U[j*n + i] = APrime[j*n + i]; for(uint8_t k = 0; k < j; k++) { U[j*n + i] -= L[j*n + k] * U[k*n + i]; } } if(j >= i) { L[j*n + i] = APrime[j*n + i]; for(uint8_t k = 0; k < i; k++) { L[j*n + i] -= L[j*n + k] * U[k*n + i]; } L[j*n + i] /= U[i*n + i]; } } } free(APrime); } /* * matrix inverse code for any square matrix using LU decomposition * inv = inv(U)*inv(L)*P, where L and U are triagular matrices and P the pivot matrix * ref: http://www.cl.cam.ac.uk/teaching/1314/NumMethods/supporting/mcmaster-kiruba-ludecomp.pdf * @param m, input 4x4 matrix * @param inv, Output inverted 4x4 matrix * @param n, dimension of square matrix * @returns false = matrix is Singular, true = matrix inversion successful */ bool mat_inverse(float* A, float* inv, uint8_t n) { float *L, *U, *P; bool ret = true; L = new float[n*n]; U = new float[n*n]; P = new float[n*n]; mat_LU_decompose(A,L,U,P,n); float *L_inv = new float[n*n]; float *U_inv = new float[n*n]; memset(L_inv,0,n*n*sizeof(float)); mat_forward_sub(L,L_inv,n); memset(U_inv,0,n*n*sizeof(float)); mat_back_sub(U,U_inv,n); // decomposed matrices no loger required free(L); free(U); float *inv_unpivoted = mat_mul(U_inv,L_inv,n); float *inv_pivoted = mat_mul(inv_unpivoted, P, n); //check sanity of results for(uint8_t i = 0; i < n; i++) { for(uint8_t j = 0; j < n; j++) { if(isnan(inv_pivoted[i*n+j]) || isinf(inv_pivoted[i*n+j])){ ret = false; } } } memcpy(inv,inv_pivoted,n*n*sizeof(float)); //free memory free(inv_pivoted); free(inv_unpivoted); free(P); return ret; } /* * fast matrix inverse code only for 3x3 square matrix * * @param m, input 4x4 matrix * @param invOut, Output inverted 4x4 matrix * @returns false = matrix is Singular, true = matrix inversion successful */ bool inverse3x3(float m[], float invOut[]) { float inv[9]; // computes the inverse of a matrix m float det = m[0] * (m[4] * m[8] - m[7] * m[5]) - m[1] * (m[3] * m[8] - m[5] * m[6]) + m[2] * (m[3] * m[7] - m[4] * m[6]); if (is_zero(det)){ return false; } float invdet = 1 / det; inv[0] = (m[4] * m[8] - m[7] * m[5]) * invdet; inv[1] = (m[2] * m[7] - m[1] * m[8]) * invdet; inv[2] = (m[1] * m[5] - m[2] * m[4]) * invdet; inv[3] = (m[5] * m[6] - m[3] * m[8]) * invdet; inv[4] = (m[0] * m[8] - m[2] * m[6]) * invdet; inv[5] = (m[3] * m[2] - m[0] * m[5]) * invdet; inv[6] = (m[3] * m[7] - m[6] * m[4]) * invdet; inv[7] = (m[6] * m[1] - m[0] * m[7]) * invdet; inv[8] = (m[0] * m[4] - m[3] * m[1]) * invdet; for(uint8_t i = 0; i < 9; i++){ invOut[i] = inv[i]; } return true; } /* * fast matrix inverse code only for 4x4 square matrix copied from * gluInvertMatrix implementation in opengl for 4x4 matrices. * * @param m, input 4x4 matrix * @param invOut, Output inverted 4x4 matrix * @returns false = matrix is Singular, true = matrix inversion successful */ bool inverse4x4(float m[],float invOut[]) { float inv[16], det; uint8_t i; inv[0] = m[5] * m[10] * m[15] - m[5] * m[11] * m[14] - m[9] * m[6] * m[15] + m[9] * m[7] * m[14] + m[13] * m[6] * m[11] - m[13] * m[7] * m[10]; inv[4] = -m[4] * m[10] * m[15] + m[4] * m[11] * m[14] + m[8] * m[6] * m[15] - m[8] * m[7] * m[14] - m[12] * m[6] * m[11] + m[12] * m[7] * m[10]; inv[8] = m[4] * m[9] * m[15] - m[4] * m[11] * m[13] - m[8] * m[5] * m[15] + m[8] * m[7] * m[13] + m[12] * m[5] * m[11] - m[12] * m[7] * m[9]; inv[12] = -m[4] * m[9] * m[14] + m[4] * m[10] * m[13] + m[8] * m[5] * m[14] - m[8] * m[6] * m[13] - m[12] * m[5] * m[10] + m[12] * m[6] * m[9]; inv[1] = -m[1] * m[10] * m[15] + m[1] * m[11] * m[14] + m[9] * m[2] * m[15] - m[9] * m[3] * m[14] - m[13] * m[2] * m[11] + m[13] * m[3] * m[10]; inv[5] = m[0] * m[10] * m[15] - m[0] * m[11] * m[14] - m[8] * m[2] * m[15] + m[8] * m[3] * m[14] + m[12] * m[2] * m[11] - m[12] * m[3] * m[10]; inv[9] = -m[0] * m[9] * m[15] + m[0] * m[11] * m[13] + m[8] * m[1] * m[15] - m[8] * m[3] * m[13] - m[12] * m[1] * m[11] + m[12] * m[3] * m[9]; inv[13] = m[0] * m[9] * m[14] - m[0] * m[10] * m[13] - m[8] * m[1] * m[14] + m[8] * m[2] * m[13] + m[12] * m[1] * m[10] - m[12] * m[2] * m[9]; inv[2] = m[1] * m[6] * m[15] - m[1] * m[7] * m[14] - m[5] * m[2] * m[15] + m[5] * m[3] * m[14] + m[13] * m[2] * m[7] - m[13] * m[3] * m[6]; inv[6] = -m[0] * m[6] * m[15] + m[0] * m[7] * m[14] + m[4] * m[2] * m[15] - m[4] * m[3] * m[14] - m[12] * m[2] * m[7] + m[12] * m[3] * m[6]; inv[10] = m[0] * m[5] * m[15] - m[0] * m[7] * m[13] - m[4] * m[1] * m[15] + m[4] * m[3] * m[13] + m[12] * m[1] * m[7] - m[12] * m[3] * m[5]; inv[14] = -m[0] * m[5] * m[14] + m[0] * m[6] * m[13] + m[4] * m[1] * m[14] - m[4] * m[2] * m[13] - m[12] * m[1] * m[6] + m[12] * m[2] * m[5]; inv[3] = -m[1] * m[6] * m[11] + m[1] * m[7] * m[10] + m[5] * m[2] * m[11] - m[5] * m[3] * m[10] - m[9] * m[2] * m[7] + m[9] * m[3] * m[6]; inv[7] = m[0] * m[6] * m[11] - m[0] * m[7] * m[10] - m[4] * m[2] * m[11] + m[4] * m[3] * m[10] + m[8] * m[2] * m[7] - m[8] * m[3] * m[6]; inv[11] = -m[0] * m[5] * m[11] + m[0] * m[7] * m[9] + m[4] * m[1] * m[11] - m[4] * m[3] * m[9] - m[8] * m[1] * m[7] + m[8] * m[3] * m[5]; inv[15] = m[0] * m[5] * m[10] - m[0] * m[6] * m[9] - m[4] * m[1] * m[10] + m[4] * m[2] * m[9] + m[8] * m[1] * m[6] - m[8] * m[2] * m[5]; det = m[0] * inv[0] + m[1] * inv[4] + m[2] * inv[8] + m[3] * inv[12]; if (is_zero(det)){ return false; } det = 1.0f / det; for (i = 0; i < 16; i++) invOut[i] = inv[i] * det; return true; } /* * generic matrix inverse code * * @param x, input nxn matrix * @param y, Output inverted nxn matrix * @param n, dimension of square matrix * @returns false = matrix is Singular, true = matrix inversion successful */ bool inverse(float x[], float y[], uint16_t dim) { switch(dim){ case 3: return inverse3x3(x,y); case 4: return inverse4x4(x,y); default: return mat_inverse(x,y,dim); } }