/* * Copyright (C) 2011 The Android Open Source Project * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ #include #include #include "Fusion.h" namespace android { // ----------------------------------------------------------------------- /* * gyroVAR gives the measured variance of the gyro's output per * Hz (or variance at 1 Hz). This is an "intrinsic" parameter of the gyro, * which is independent of the sampling frequency. * * The variance of gyro's output at a given sampling period can be * calculated as: * variance(T) = gyroVAR / T * * The variance of the INTEGRATED OUTPUT at a given sampling period can be * calculated as: * variance_integrate_output(T) = gyroVAR * T * */ static const float gyroVAR = 1e-7; // (rad/s)^2 / Hz static const float biasVAR = 1e-8; // (rad/s)^2 / s (guessed) /* * Standard deviations of accelerometer and magnetometer */ static const float accSTDEV = 0.05f; // m/s^2 (measured 0.08 / CDD 0.05) static const float magSTDEV = 0.5f; // uT (measured 0.7 / CDD 0.5) static const float SYMMETRY_TOLERANCE = 1e-10f; /* * Accelerometer updates will not be performed near free fall to avoid * ill-conditioning and div by zeros. * Threshhold: 10% of g, in m/s^2 */ static const float FREE_FALL_THRESHOLD = 0.981f; static const float FREE_FALL_THRESHOLD_SQ = FREE_FALL_THRESHOLD*FREE_FALL_THRESHOLD; /* * The geomagnetic-field should be between 30uT and 60uT. * Fields strengths greater than this likely indicate a local magnetic * disturbance which we do not want to update into the fused frame. */ static const float MAX_VALID_MAGNETIC_FIELD = 100; // uT static const float MAX_VALID_MAGNETIC_FIELD_SQ = MAX_VALID_MAGNETIC_FIELD*MAX_VALID_MAGNETIC_FIELD; /* * Values of the field smaller than this should be ignored in fusion to avoid * ill-conditioning. This state can happen with anomalous local magnetic * disturbances canceling the Earth field. */ static const float MIN_VALID_MAGNETIC_FIELD = 10; // uT static const float MIN_VALID_MAGNETIC_FIELD_SQ = MIN_VALID_MAGNETIC_FIELD*MIN_VALID_MAGNETIC_FIELD; /* * If the cross product of two vectors has magnitude squared less than this, * we reject it as invalid due to alignment of the vectors. * This threshold is used to check for the case where the magnetic field sample * is parallel to the gravity field, which can happen in certain places due * to magnetic field disturbances. */ static const float MIN_VALID_CROSS_PRODUCT_MAG = 1.0e-3; static const float MIN_VALID_CROSS_PRODUCT_MAG_SQ = MIN_VALID_CROSS_PRODUCT_MAG*MIN_VALID_CROSS_PRODUCT_MAG; // ----------------------------------------------------------------------- template static mat scaleCovariance( const mat& A, const mat& P) { // A*P*transpose(A); mat APAt; for (size_t r=0 ; r static mat crossMatrix(const vec& p, OTHER_TYPE diag) { mat r; r[0][0] = diag; r[1][1] = diag; r[2][2] = diag; r[0][1] = p.z; r[1][0] =-p.z; r[0][2] =-p.y; r[2][0] = p.y; r[1][2] = p.x; r[2][1] =-p.x; return r; } template class Covariance { mat mSumXX; vec mSumX; size_t mN; public: Covariance() : mSumXX(0.0f), mSumX(0.0f), mN(0) { } void update(const vec& x) { mSumXX += x*transpose(x); mSumX += x; mN++; } mat operator()() const { const float N = 1.0f / mN; return mSumXX*N - (mSumX*transpose(mSumX))*(N*N); } void reset() { mN = 0; mSumXX = 0; mSumX = 0; } size_t getCount() const { return mN; } }; // ----------------------------------------------------------------------- Fusion::Fusion() { Phi[0][1] = 0; Phi[1][1] = 1; Ba.x = 0; Ba.y = 0; Ba.z = 1; Bm.x = 0; Bm.y = 1; Bm.z = 0; x0 = 0; x1 = 0; init(); } void Fusion::init() { mInitState = 0; mGyroRate = 0; mCount[0] = 0; mCount[1] = 0; mCount[2] = 0; mData = 0; } void Fusion::initFusion(const vec4_t& q, float dT) { // initial estimate: E{ x(t0) } x0 = q; x1 = 0; // process noise covariance matrix: G.Q.Gt, with // // G = | -1 0 | Q = | q00 q10 | // | 0 1 | | q01 q11 | // // q00 = sv^2.dt + 1/3.su^2.dt^3 // q10 = q01 = 1/2.su^2.dt^2 // q11 = su^2.dt // // variance of integrated output at 1/dT Hz // (random drift) const float q00 = gyroVAR * dT; // variance of drift rate ramp const float q11 = biasVAR * dT; const float u = q11 / dT; const float q10 = 0.5f*u*dT*dT; const float q01 = q10; GQGt[0][0] = q00; // rad^2 GQGt[1][0] = -q10; GQGt[0][1] = -q01; GQGt[1][1] = q11; // (rad/s)^2 // initial covariance: Var{ x(t0) } // TODO: initialize P correctly P = 0; } bool Fusion::hasEstimate() const { return (mInitState == (MAG|ACC|GYRO)); } bool Fusion::checkInitComplete(int what, const vec3_t& d, float dT) { if (hasEstimate()) return true; if (what == ACC) { mData[0] += d * (1/length(d)); mCount[0]++; mInitState |= ACC; } else if (what == MAG) { mData[1] += d * (1/length(d)); mCount[1]++; mInitState |= MAG; } else if (what == GYRO) { mGyroRate = dT; mData[2] += d*dT; mCount[2]++; if (mCount[2] == 64) { // 64 samples is good enough to estimate the gyro drift and // doesn't take too much time. mInitState |= GYRO; } } if (mInitState == (MAG|ACC|GYRO)) { // Average all the values we collected so far mData[0] *= 1.0f/mCount[0]; mData[1] *= 1.0f/mCount[1]; mData[2] *= 1.0f/mCount[2]; // calculate the MRPs from the data collection, this gives us // a rough estimate of our initial state mat33_t R; vec3_t up(mData[0]); vec3_t east(cross_product(mData[1], up)); east *= 1/length(east); vec3_t north(cross_product(up, east)); R << east << north << up; const vec4_t q = matrixToQuat(R); initFusion(q, mGyroRate); } return false; } void Fusion::handleGyro(const vec3_t& w, float dT) { if (!checkInitComplete(GYRO, w, dT)) return; predict(w, dT); } status_t Fusion::handleAcc(const vec3_t& a) { // ignore acceleration data if we're close to free-fall if (length_squared(a) < FREE_FALL_THRESHOLD_SQ) { return BAD_VALUE; } if (!checkInitComplete(ACC, a)) return BAD_VALUE; const float l = 1/length(a); update(a*l, Ba, accSTDEV*l); return NO_ERROR; } status_t Fusion::handleMag(const vec3_t& m) { // the geomagnetic-field should be between 30uT and 60uT // reject if too large to avoid spurious magnetic sources const float magFieldSq = length_squared(m); if (magFieldSq > MAX_VALID_MAGNETIC_FIELD_SQ) { return BAD_VALUE; } else if (magFieldSq < MIN_VALID_MAGNETIC_FIELD_SQ) { // Also reject if too small since we will get ill-defined (zero mag) // cross-products below return BAD_VALUE; } if (!checkInitComplete(MAG, m)) return BAD_VALUE; // Orthogonalize the magnetic field to the gravity field, mapping it into // tangent to Earth. const vec3_t up( getRotationMatrix() * Ba ); const vec3_t east( cross_product(m, up) ); // If the m and up vectors align, the cross product magnitude will // approach 0. // Reject this case as well to avoid div by zero problems and // ill-conditioning below. if (length_squared(east) < MIN_VALID_CROSS_PRODUCT_MAG_SQ) { return BAD_VALUE; } // If we have created an orthogonal magnetic field successfully, // then pass it in as the update. vec3_t north( cross_product(up, east) ); const float l = 1 / length(north); north *= l; update(north, Bm, magSTDEV*l); return NO_ERROR; } void Fusion::checkState() { // P needs to stay positive semidefinite or the fusion diverges. When we // detect divergence, we reset the fusion. // TODO(braun): Instead, find the reason for the divergence and fix it. if (!isPositiveSemidefinite(P[0][0], SYMMETRY_TOLERANCE) || !isPositiveSemidefinite(P[1][1], SYMMETRY_TOLERANCE)) { LOGW("Sensor fusion diverged; resetting state."); P = 0; } } vec4_t Fusion::getAttitude() const { return x0; } vec3_t Fusion::getBias() const { return x1; } mat33_t Fusion::getRotationMatrix() const { return quatToMatrix(x0); } mat34_t Fusion::getF(const vec4_t& q) { mat34_t F; F[0].x = q.w; F[1].x =-q.z; F[2].x = q.y; F[0].y = q.z; F[1].y = q.w; F[2].y =-q.x; F[0].z =-q.y; F[1].z = q.x; F[2].z = q.w; F[0].w =-q.x; F[1].w =-q.y; F[2].w =-q.z; return F; } void Fusion::predict(const vec3_t& w, float dT) { const vec4_t q = x0; const vec3_t b = x1; const vec3_t we = w - b; const vec4_t dq = getF(q)*((0.5f*dT)*we); x0 = normalize_quat(q + dq); // P(k+1) = F*P(k)*Ft + G*Q*Gt // Phi = | Phi00 Phi10 | // | 0 1 | const mat33_t I33(1); const mat33_t I33dT(dT); const mat33_t wx(crossMatrix(we, 0)); const mat33_t wx2(wx*wx); const float lwedT = length(we)*dT; const float ilwe = 1/length(we); const float k0 = (1-cosf(lwedT))*(ilwe*ilwe); const float k1 = sinf(lwedT); Phi[0][0] = I33 - wx*(k1*ilwe) + wx2*k0; Phi[1][0] = wx*k0 - I33dT - wx2*(ilwe*ilwe*ilwe)*(lwedT-k1); P = Phi*P*transpose(Phi) + GQGt; checkState(); } void Fusion::update(const vec3_t& z, const vec3_t& Bi, float sigma) { vec4_t q(x0); // measured vector in body space: h(p) = A(p)*Bi const mat33_t A(quatToMatrix(q)); const vec3_t Bb(A*Bi); // Sensitivity matrix H = dh(p)/dp // H = [ L 0 ] const mat33_t L(crossMatrix(Bb, 0)); // gain... // K = P*Ht / [H*P*Ht + R] vec K; const mat33_t R(sigma*sigma); const mat33_t S(scaleCovariance(L, P[0][0]) + R); const mat33_t Si(invert(S)); const mat33_t LtSi(transpose(L)*Si); K[0] = P[0][0] * LtSi; K[1] = transpose(P[1][0])*LtSi; // update... // P -= K*H*P; const mat33_t K0L(K[0] * L); const mat33_t K1L(K[1] * L); P[0][0] -= K0L*P[0][0]; P[1][1] -= K1L*P[1][0]; P[1][0] -= K0L*P[1][0]; P[0][1] = transpose(P[1][0]); const vec3_t e(z - Bb); const vec3_t dq(K[0]*e); const vec3_t db(K[1]*e); q += getF(q)*(0.5f*dq); x0 = normalize_quat(q); x1 += db; checkState(); } // ----------------------------------------------------------------------- }; // namespace android