diff options
Diffstat (limited to 'services/sensorservice/Fusion.cpp')
| -rw-r--r-- | services/sensorservice/Fusion.cpp | 65 |
1 files changed, 56 insertions, 9 deletions
diff --git a/services/sensorservice/Fusion.cpp b/services/sensorservice/Fusion.cpp index b88a647..93d6127 100644 --- a/services/sensorservice/Fusion.cpp +++ b/services/sensorservice/Fusion.cpp @@ -201,15 +201,15 @@ void Fusion::initFusion(const vec4_t& q, float dT) // q11 = su^2.dt // - // variance of integrated output at 1/dT Hz - // (random drift) - const float q00 = gyroVAR * dT; + const float dT2 = dT*dT; + const float dT3 = dT2*dT; + + // variance of integrated output at 1/dT Hz (random drift) + const float q00 = gyroVAR * dT + 0.33333f * biasVAR * dT3; // 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 q10 = 0.5f * biasVAR * dT2; const float q01 = q10; GQGt[0][0] = q00; // rad^2 @@ -220,6 +220,22 @@ void Fusion::initFusion(const vec4_t& q, float dT) // initial covariance: Var{ x(t0) } // TODO: initialize P correctly P = 0; + + // it is unclear how to set the initial covariance. It does affect + // how quickly the fusion converges. Experimentally it would take + // about 10 seconds at 200 Hz to estimate the gyro-drift with an + // initial covariance of 0, and about a second with an initial covariance + // of about 1 deg/s. + const float covv = 0; + const float covu = 0.5f * (float(M_PI) / 180); + mat33_t& Pv = P[0][0]; + Pv[0][0] = covv; + Pv[1][1] = covv; + Pv[2][2] = covv; + mat33_t& Pu = P[1][1]; + Pu[0][0] = covu; + Pu[1][1] = covu; + Pu[2][2] = covu; } bool Fusion::hasEstimate() const { @@ -357,6 +373,11 @@ mat33_t Fusion::getRotationMatrix() const { mat34_t Fusion::getF(const vec4_t& q) { mat34_t F; + + // This is used to compute the derivative of q + // F = | [q.xyz]x | + // | -q.xyz | + 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; @@ -368,10 +389,18 @@ 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); + // q(k+1) = O(we)*q(k) + // -------------------- + // + // O(w) = | cos(0.5*||w||*dT)*I33 - [psi]x psi | + // | -psi' cos(0.5*||w||*dT) | + // + // psi = sin(0.5*||w||*dT)*w / ||w|| + // + // // P(k+1) = Phi(k)*P(k)*Phi(k)' + G*Q(k)*G' + // ---------------------------------------- // // G = | -I33 0 | // | 0 I33 | @@ -392,13 +421,26 @@ void Fusion::predict(const vec3_t& w, float dT) { const mat33_t wx(crossMatrix(we, 0)); const mat33_t wx2(wx*wx); const float lwedT = length(we)*dT; + const float hlwedT = 0.5f*lwedT; const float ilwe = 1/length(we); const float k0 = (1-cosf(lwedT))*(ilwe*ilwe); const float k1 = sinf(lwedT); + const float k2 = cosf(hlwedT); + const vec3_t psi(sinf(hlwedT)*ilwe*we); + const mat33_t O33(crossMatrix(-psi, k2)); + mat44_t O; + O[0].xyz = O33[0]; O[0].w = -psi.x; + O[1].xyz = O33[1]; O[1].w = -psi.y; + O[2].xyz = O33[2]; O[2].w = -psi.z; + O[3].xyz = psi; O[3].w = k2; Phi[0][0] = I33 - wx*(k1*ilwe) + wx2*k0; Phi[1][0] = wx*k0 - I33dT - wx2*(ilwe*ilwe*ilwe)*(lwedT-k1); + x0 = O*q; + if (x0.w < 0) + x0 = -x0; + P = Phi*P*transpose(Phi) + GQGt; checkState(); @@ -425,7 +467,12 @@ void Fusion::update(const vec3_t& z, const vec3_t& Bi, float sigma) { K[1] = transpose(P[1][0])*LtSi; // update... - // P -= K*H*P; + // P = (I-K*H) * P + // P -= K*H*P + // | K0 | * | L 0 | * P = | K0*L 0 | * | P00 P10 | = | K0*L*P00 K0*L*P10 | + // | K1 | | K1*L 0 | | P01 P11 | | K1*L*P00 K1*L*P10 | + // Note: the Joseph form is numerically more stable and given by: + // P = (I-KH) * P * (I-KH)' + K*R*R' const mat33_t K0L(K[0] * L); const mat33_t K1L(K[1] * L); P[0][0] -= K0L*P[0][0]; |