forked from Archive/PX4-Autopilot
ekf2: compute quat tilt variance using SymForce
This commit is contained in:
bresch
Daniel Agar
parent
af40d5befd
commit
0282f85cd4
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@ -43,6 +43,7 @@
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#include "ekf.h"
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#include "python/ekf_derivation/generated/predict_covariance.h"
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#include "python/ekf_derivation/generated/rot_var_ned_to_lower_triangular_quat_cov.h"
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#include <math.h>
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#include <mathlib/mathlib.h>
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@ -53,7 +54,7 @@ void Ekf::initialiseCovariance()
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{
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P.zero();
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resetQuatCov();
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resetQuatCov((_params.mag_fusion_type != MagFuseType::NONE) ?_params.mag_heading_noise : NAN);
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// velocity
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P(4,4) = sq(fmaxf(_params.gps_vel_noise, 0.01f));
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@ -526,27 +527,25 @@ bool Ekf::checkAndFixCovarianceUpdate(const SquareMatrix24f &KHP)
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return healthy;
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}
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void Ekf::resetQuatCov()
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void Ekf::resetQuatCov(const float yaw_noise)
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{
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zeroQuatCov();
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// define the initial angle uncertainty as variances for a rotation vector
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Vector3f rot_vec_var;
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rot_vec_var.setAll(sq(_params.initial_tilt_err));
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initialiseQuatCovariances(rot_vec_var);
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const float tilt_var = sq(fmaxf(_params.initial_tilt_err, 1.0e-2f));
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Vector3f rot_var_ned(tilt_var, tilt_var, 0.f);
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// update the yaw angle variance using the variance of the measurement
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if (_params.mag_fusion_type != MagFuseType::NONE) {
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if (PX4_ISFINITE(yaw_noise)) {
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// using magnetic heading tuning parameter
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increaseQuatYawErrVariance(sq(fmaxf(_params.mag_heading_noise, 1.0e-2f)));
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rot_var_ned(2) = (sq(fmaxf(yaw_noise, 1.0e-2f)));
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}
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}
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void Ekf::zeroQuatCov()
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{
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// clear existing quaternion covariance
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P.uncorrelateCovarianceSetVariance<2>(0, 0.0f);
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P.uncorrelateCovarianceSetVariance<2>(2, 0.0f);
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matrix::SquareMatrix<float, 4> q_cov;
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sym::RotVarNedToLowerTriangularQuatCov(getStateAtFusionHorizonAsVector(), rot_var_ned, &q_cov);
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q_cov.copyLowerToUpperTriangle();
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P.slice<4, 4>(0, 0) = q_cov;
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}
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void Ekf::resetMagCov()
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@ -1075,12 +1075,7 @@ private:
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// gravity fusion: heuristically enable / disable gravity fusion
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void controlGravityFusion(const imuSample &imu_delayed);
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// initialise the quaternion covariances using rotation vector variances
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// do not call before quaternion states are initialised
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void initialiseQuatCovariances(Vector3f &rot_vec_var);
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void resetQuatCov();
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void zeroQuatCov();
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void resetQuatCov(float yaw_noise = NAN);
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void resetMagCov();
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@ -41,7 +41,7 @@
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#include "ekf.h"
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#include "python/ekf_derivation/generated/quat_var_to_rot_var.h"
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#include "python/ekf_derivation/generated/yaw_var_to_lower_triangular_quat_cov.h"
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#include "python/ekf_derivation/generated/rot_var_ned_to_lower_triangular_quat_cov.h"
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#include <mathlib/mathlib.h>
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#include <lib/world_magnetic_model/geo_mag_declination.h>
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@ -917,106 +917,6 @@ float Ekf::getYawVar() const
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return yaw_var;
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}
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// initialise the quaternion covariances using rotation vector variances
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// do not call before quaternion states are initialised
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void Ekf::initialiseQuatCovariances(Vector3f &rot_vec_var)
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{
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// calculate an equivalent rotation vector from the quaternion
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float q0,q1,q2,q3;
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if (_state.quat_nominal(0) >= 0.0f) {
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q0 = _state.quat_nominal(0);
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q1 = _state.quat_nominal(1);
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q2 = _state.quat_nominal(2);
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q3 = _state.quat_nominal(3);
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} else {
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q0 = -_state.quat_nominal(0);
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q1 = -_state.quat_nominal(1);
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q2 = -_state.quat_nominal(2);
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q3 = -_state.quat_nominal(3);
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}
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float delta = 2.0f*acosf(q0);
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float scaler = (delta/sinf(delta*0.5f));
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float rotX = scaler*q1;
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float rotY = scaler*q2;
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float rotZ = scaler*q3;
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// autocode generated using matlab symbolic toolbox
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float t2 = rotX*rotX;
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float t4 = rotY*rotY;
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float t5 = rotZ*rotZ;
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float t6 = t2+t4+t5;
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if (t6 > 1e-9f) {
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float t7 = sqrtf(t6);
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float t8 = t7*0.5f;
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float t3 = sinf(t8);
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float t9 = t3*t3;
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float t10 = 1.0f/t6;
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float t11 = 1.0f/sqrtf(t6);
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float t12 = cosf(t8);
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float t13 = 1.0f/powf(t6,1.5f);
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float t14 = t3*t11;
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float t15 = rotX*rotY*t3*t13;
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float t16 = rotX*rotZ*t3*t13;
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float t17 = rotY*rotZ*t3*t13;
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float t18 = t2*t10*t12*0.5f;
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float t27 = t2*t3*t13;
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float t19 = t14+t18-t27;
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float t23 = rotX*rotY*t10*t12*0.5f;
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float t28 = t15-t23;
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float t20 = rotY*rot_vec_var(1)*t3*t11*t28*0.5f;
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float t25 = rotX*rotZ*t10*t12*0.5f;
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float t31 = t16-t25;
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float t21 = rotZ*rot_vec_var(2)*t3*t11*t31*0.5f;
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float t22 = t20+t21-rotX*rot_vec_var(0)*t3*t11*t19*0.5f;
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float t24 = t15-t23;
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float t26 = t16-t25;
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float t29 = t4*t10*t12*0.5f;
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float t34 = t3*t4*t13;
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float t30 = t14+t29-t34;
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float t32 = t5*t10*t12*0.5f;
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float t40 = t3*t5*t13;
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float t33 = t14+t32-t40;
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float t36 = rotY*rotZ*t10*t12*0.5f;
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float t39 = t17-t36;
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float t35 = rotZ*rot_vec_var(2)*t3*t11*t39*0.5f;
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float t37 = t15-t23;
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float t38 = t17-t36;
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float t41 = rot_vec_var(0)*(t15-t23)*(t16-t25);
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float t42 = t41-rot_vec_var(1)*t30*t39-rot_vec_var(2)*t33*t39;
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float t43 = t16-t25;
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float t44 = t17-t36;
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// zero all the quaternion covariances
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P.uncorrelateCovarianceSetVariance<2>(0, 0.0f);
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P.uncorrelateCovarianceSetVariance<2>(2, 0.0f);
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// Update the quaternion internal covariances using auto-code generated using matlab symbolic toolbox
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P(0,0) = rot_vec_var(0)*t2*t9*t10*0.25f+rot_vec_var(1)*t4*t9*t10*0.25f+rot_vec_var(2)*t5*t9*t10*0.25f;
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P(0,1) = t22;
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P(0,2) = t35+rotX*rot_vec_var(0)*t3*t11*(t15-rotX*rotY*t10*t12*0.5f)*0.5f-rotY*rot_vec_var(1)*t3*t11*t30*0.5f;
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P(0,3) = rotX*rot_vec_var(0)*t3*t11*(t16-rotX*rotZ*t10*t12*0.5f)*0.5f+rotY*rot_vec_var(1)*t3*t11*(t17-rotY*rotZ*t10*t12*0.5f)*0.5f-rotZ*rot_vec_var(2)*t3*t11*t33*0.5f;
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P(1,0) = t22;
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P(1,1) = rot_vec_var(0)*(t19*t19)+rot_vec_var(1)*(t24*t24)+rot_vec_var(2)*(t26*t26);
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P(1,2) = rot_vec_var(2)*(t16-t25)*(t17-rotY*rotZ*t10*t12*0.5f)-rot_vec_var(0)*t19*t28-rot_vec_var(1)*t28*t30;
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P(1,3) = rot_vec_var(1)*(t15-t23)*(t17-rotY*rotZ*t10*t12*0.5f)-rot_vec_var(0)*t19*t31-rot_vec_var(2)*t31*t33;
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P(2,0) = t35-rotY*rot_vec_var(1)*t3*t11*t30*0.5f+rotX*rot_vec_var(0)*t3*t11*(t15-t23)*0.5f;
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P(2,1) = rot_vec_var(2)*(t16-t25)*(t17-t36)-rot_vec_var(0)*t19*t28-rot_vec_var(1)*t28*t30;
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P(2,2) = rot_vec_var(1)*(t30*t30)+rot_vec_var(0)*(t37*t37)+rot_vec_var(2)*(t38*t38);
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P(2,3) = t42;
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P(3,0) = rotZ*rot_vec_var(2)*t3*t11*t33*(-0.5f)+rotX*rot_vec_var(0)*t3*t11*(t16-t25)*0.5f+rotY*rot_vec_var(1)*t3*t11*(t17-t36)*0.5f;
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P(3,1) = rot_vec_var(1)*(t15-t23)*(t17-t36)-rot_vec_var(0)*t19*t31-rot_vec_var(2)*t31*t33;
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P(3,2) = t42;
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P(3,3) = rot_vec_var(2)*(t33*t33)+rot_vec_var(0)*(t43*t43)+rot_vec_var(1)*(t44*t44);
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} else {
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// the equations are badly conditioned so use a small angle approximation
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P.uncorrelateCovarianceSetVariance<1>(0, 0.0f);
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P.uncorrelateCovarianceSetVariance<3>(1, 0.25f * rot_vec_var);
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}
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}
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void Ekf::updateGroundEffect()
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{
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if (_control_status.flags.in_air && !_control_status.flags.fixed_wing) {
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@ -1040,7 +940,7 @@ void Ekf::updateGroundEffect()
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void Ekf::increaseQuatYawErrVariance(float yaw_variance)
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{
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matrix::SquareMatrix<float, 4> q_cov;
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sym::YawVarToLowerTriangularQuatCov(getStateAtFusionHorizonAsVector(), yaw_variance, &q_cov);
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sym::RotVarNedToLowerTriangularQuatCov(getStateAtFusionHorizonAsVector(), Vector3f(0.f, 0.f, yaw_variance), &q_cov);
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q_cov.copyLowerToUpperTriangle();
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P.slice<4, 4>(0, 0) += q_cov;
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}
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@ -76,7 +76,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
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// we need to re-initialise covariances and abort this fusion step
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if (update_all_states) {
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resetQuatCov();
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resetQuatCov(_params.mag_heading_noise);
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}
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resetMagCov();
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@ -94,7 +94,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
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// we need to re-initialise covariances and abort this fusion step
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if (update_all_states) {
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resetQuatCov();
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resetQuatCov(_params.mag_heading_noise);
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}
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resetMagCov();
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@ -111,7 +111,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
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// we need to re-initialise covariances and abort this fusion step
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if (update_all_states) {
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resetQuatCov();
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resetQuatCov(_params.mag_heading_noise);
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}
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resetMagCov();
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@ -175,7 +175,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
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// we need to re-initialise covariances and abort this fusion step
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if (update_all_states) {
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resetQuatCov();
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resetQuatCov(_params.mag_heading_noise);
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}
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resetMagCov();
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@ -204,7 +204,7 @@ bool Ekf::fuseMag(const Vector3f &mag, estimator_aid_source3d_s &aid_src_mag, bo
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// we need to re-initialise covariances and abort this fusion step
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if (update_all_states) {
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resetQuatCov();
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resetQuatCov(_params.mag_heading_noise);
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}
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resetMagCov();
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@ -511,21 +511,25 @@ def quat_var_to_rot_var(
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rot_cov = J * P * J.T
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return sf.V3(rot_cov[0, 0], rot_cov[1, 1], rot_cov[2, 2])
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def yaw_var_to_lower_triangular_quat_cov(
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def rot_var_ned_to_lower_triangular_quat_cov(
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state: VState,
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yaw_var: sf.Scalar
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rot_var_ned: sf.V3
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):
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# This function converts an attitude variance defined by a 3D vector in NED frame
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# into a 4x4 covariance matrix representing the uncertainty on each of the 4 quaternion parameters
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# Note: the resulting quaternion uncertainty is defined as a perturbation
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# at the tip of the quaternion (i.e.:body-frame uncertainty)
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q = sf.V4(state[State.qw], state[State.qx], state[State.qy], state[State.qz])
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attitude = state_to_rot3(state)
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J = q.jacobian(attitude)
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# Convert yaw uncertainty from NED to body frame
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yaw_cov_ned = sf.M33.diag([0, 0, yaw_var])
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# Convert uncertainties from NED to body frame
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rot_cov_ned = sf.M33.diag(rot_var_ned)
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adjoint = attitude.to_rotation_matrix() # the adjoint of SO(3) is simply the rotation matrix itself
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yaw_cov_body = adjoint.T * yaw_cov_ned * adjoint
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rot_cov_body = adjoint.T * rot_cov_ned * adjoint
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# Convert yaw (body) to quaternion parameter uncertainty
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q_var = J * yaw_cov_body * J.T
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q_var = J * rot_cov_body * J.T
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# Generate lower trangle only and copy it to the upper part in implementation (produces less code)
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return q_var.lower_triangle()
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@ -552,4 +556,4 @@ generate_px4_function(compute_drag_x_innov_var_and_k, output_names=["innov_var",
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generate_px4_function(compute_drag_y_innov_var_and_k, output_names=["innov_var", "K"])
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generate_px4_function(compute_gravity_innov_var_and_k_and_h, output_names=["innov", "innov_var", "Kx", "Ky", "Kz"])
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generate_px4_function(quat_var_to_rot_var, output_names=["rot_var"])
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generate_px4_function(yaw_var_to_lower_triangular_quat_cov, output_names=["q_cov_lower_triangle"])
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generate_px4_function(rot_var_ned_to_lower_triangular_quat_cov, output_names=["q_cov_lower_triangle"])
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@ -0,0 +1,123 @@
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// -----------------------------------------------------------------------------
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// This file was autogenerated by symforce from template:
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// function/FUNCTION.h.jinja
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// Do NOT modify by hand.
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// -----------------------------------------------------------------------------
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#pragma once
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#include <matrix/math.hpp>
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namespace sym {
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/**
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* This function was autogenerated from a symbolic function. Do not modify by hand.
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*
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* Symbolic function: rot_var_ned_to_lower_triangular_quat_cov
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*
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* Args:
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* state: Matrix24_1
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* rot_var_ned: Matrix31
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*
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* Outputs:
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* q_cov_lower_triangle: Matrix44
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*/
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template <typename Scalar>
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void RotVarNedToLowerTriangularQuatCov(
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const matrix::Matrix<Scalar, 24, 1>& state, const matrix::Matrix<Scalar, 3, 1>& rot_var_ned,
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matrix::Matrix<Scalar, 4, 4>* const q_cov_lower_triangle = nullptr) {
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// Total ops: 185
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// Input arrays
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// Intermediate terms (54)
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const Scalar _tmp0 = 2 * state(0, 0) * state(2, 0);
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const Scalar _tmp1 = 2 * state(3, 0);
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const Scalar _tmp2 = _tmp1 * state(1, 0);
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const Scalar _tmp3 = _tmp0 + _tmp2;
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const Scalar _tmp4 = _tmp1 * state(0, 0);
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const Scalar _tmp5 = 2 * state(1, 0);
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const Scalar _tmp6 = _tmp5 * state(2, 0);
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const Scalar _tmp7 = -_tmp4 + _tmp6;
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const Scalar _tmp8 = -2 * std::pow(state(3, 0), Scalar(2));
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const Scalar _tmp9 = -2 * std::pow(state(1, 0), Scalar(2));
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const Scalar _tmp10 = _tmp8 + _tmp9 + 1;
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const Scalar _tmp11 = _tmp1 * state(2, 0);
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const Scalar _tmp12 = _tmp5 * state(0, 0);
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const Scalar _tmp13 = _tmp11 - _tmp12;
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const Scalar _tmp14 = _tmp13 * rot_var_ned(1, 0);
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const Scalar _tmp15 = 1 - 2 * std::pow(state(2, 0), Scalar(2));
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const Scalar _tmp16 = _tmp15 + _tmp9;
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const Scalar _tmp17 = _tmp11 + _tmp12;
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const Scalar _tmp18 = _tmp17 * rot_var_ned(2, 0);
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const Scalar _tmp19 = _tmp10 * _tmp14 + _tmp16 * _tmp18 + _tmp3 * _tmp7 * rot_var_ned(0, 0);
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const Scalar _tmp20 = (Scalar(1) / Scalar(2)) * state(3, 0);
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const Scalar _tmp21 = -_tmp19 * _tmp20;
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const Scalar _tmp22 = std::pow(_tmp10, Scalar(2)) * rot_var_ned(1, 0) +
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std::pow(_tmp17, Scalar(2)) * rot_var_ned(2, 0) +
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std::pow(_tmp7, Scalar(2)) * rot_var_ned(0, 0);
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const Scalar _tmp23 = (Scalar(1) / Scalar(2)) * state(2, 0);
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const Scalar _tmp24 = _tmp15 + _tmp8;
|
||||
const Scalar _tmp25 = _tmp24 * rot_var_ned(0, 0);
|
||||
const Scalar _tmp26 = _tmp4 + _tmp6;
|
||||
const Scalar _tmp27 = -_tmp0 + _tmp2;
|
||||
const Scalar _tmp28 = (Scalar(1) / Scalar(2)) * _tmp10 * _tmp26 * rot_var_ned(1, 0) +
|
||||
(Scalar(1) / Scalar(2)) * _tmp18 * _tmp27 +
|
||||
(Scalar(1) / Scalar(2)) * _tmp25 * _tmp7;
|
||||
const Scalar _tmp29 = _tmp28 * state(1, 0);
|
||||
const Scalar _tmp30 = std::pow(_tmp24, Scalar(2)) * rot_var_ned(0, 0) +
|
||||
std::pow(_tmp26, Scalar(2)) * rot_var_ned(1, 0) +
|
||||
std::pow(_tmp27, Scalar(2)) * rot_var_ned(2, 0);
|
||||
const Scalar _tmp31 = (Scalar(1) / Scalar(2)) * state(1, 0);
|
||||
const Scalar _tmp32 = _tmp14 * _tmp26 + _tmp16 * _tmp27 * rot_var_ned(2, 0) + _tmp25 * _tmp3;
|
||||
const Scalar _tmp33 = _tmp20 * _tmp32;
|
||||
const Scalar _tmp34 = -_tmp28 * state(2, 0);
|
||||
const Scalar _tmp35 = _tmp19 * _tmp23;
|
||||
const Scalar _tmp36 = std::pow(_tmp13, Scalar(2)) * rot_var_ned(1, 0) +
|
||||
std::pow(_tmp16, Scalar(2)) * rot_var_ned(2, 0) +
|
||||
std::pow(_tmp3, Scalar(2)) * rot_var_ned(0, 0);
|
||||
const Scalar _tmp37 = -_tmp31 * _tmp32;
|
||||
const Scalar _tmp38 = _tmp28 * state(0, 0);
|
||||
const Scalar _tmp39 = -_tmp20 * _tmp22 + _tmp35 + _tmp38;
|
||||
const Scalar _tmp40 = (Scalar(1) / Scalar(2)) * state(0, 0);
|
||||
const Scalar _tmp41 = _tmp23 * _tmp32;
|
||||
const Scalar _tmp42 = _tmp28 * state(3, 0);
|
||||
const Scalar _tmp43 = _tmp30 * _tmp40 + _tmp41 - _tmp42;
|
||||
const Scalar _tmp44 = _tmp32 * _tmp40;
|
||||
const Scalar _tmp45 = _tmp21 + _tmp23 * _tmp36 + _tmp44;
|
||||
const Scalar _tmp46 = _tmp19 * _tmp31;
|
||||
const Scalar _tmp47 = _tmp22 * _tmp40 + _tmp42 - _tmp46;
|
||||
const Scalar _tmp48 = _tmp20 * _tmp30 + _tmp37 + _tmp38;
|
||||
const Scalar _tmp49 = _tmp19 * _tmp40;
|
||||
const Scalar _tmp50 = -_tmp31 * _tmp36 + _tmp33 + _tmp49;
|
||||
const Scalar _tmp51 = _tmp22 * _tmp31 + _tmp34 + _tmp49;
|
||||
const Scalar _tmp52 = -_tmp23 * _tmp30 + _tmp29 + _tmp44;
|
||||
const Scalar _tmp53 = _tmp36 * _tmp40 - _tmp41 + _tmp46;
|
||||
|
||||
// Output terms (1)
|
||||
if (q_cov_lower_triangle != nullptr) {
|
||||
matrix::Matrix<Scalar, 4, 4>& _q_cov_lower_triangle = (*q_cov_lower_triangle);
|
||||
|
||||
_q_cov_lower_triangle(0, 0) = -_tmp20 * (-_tmp20 * _tmp36 - _tmp35 + _tmp37) -
|
||||
_tmp23 * (_tmp21 - _tmp22 * _tmp23 - _tmp29) -
|
||||
_tmp31 * (-_tmp30 * _tmp31 - _tmp33 + _tmp34);
|
||||
_q_cov_lower_triangle(1, 0) = -_tmp20 * _tmp45 - _tmp23 * _tmp39 - _tmp31 * _tmp43;
|
||||
_q_cov_lower_triangle(2, 0) = -_tmp20 * _tmp50 - _tmp23 * _tmp47 - _tmp31 * _tmp48;
|
||||
_q_cov_lower_triangle(3, 0) = -_tmp20 * _tmp53 - _tmp23 * _tmp51 - _tmp31 * _tmp52;
|
||||
_q_cov_lower_triangle(0, 1) = 0;
|
||||
_q_cov_lower_triangle(1, 1) = -_tmp20 * _tmp39 + _tmp23 * _tmp45 + _tmp40 * _tmp43;
|
||||
_q_cov_lower_triangle(2, 1) = -_tmp20 * _tmp47 + _tmp23 * _tmp50 + _tmp40 * _tmp48;
|
||||
_q_cov_lower_triangle(3, 1) = -_tmp20 * _tmp51 + _tmp23 * _tmp53 + _tmp40 * _tmp52;
|
||||
_q_cov_lower_triangle(0, 2) = 0;
|
||||
_q_cov_lower_triangle(1, 2) = 0;
|
||||
_q_cov_lower_triangle(2, 2) = _tmp20 * _tmp48 - _tmp31 * _tmp50 + _tmp40 * _tmp47;
|
||||
_q_cov_lower_triangle(3, 2) = _tmp20 * _tmp52 - _tmp31 * _tmp53 + _tmp40 * _tmp51;
|
||||
_q_cov_lower_triangle(0, 3) = 0;
|
||||
_q_cov_lower_triangle(1, 3) = 0;
|
||||
_q_cov_lower_triangle(2, 3) = 0;
|
||||
_q_cov_lower_triangle(3, 3) = -_tmp23 * _tmp52 + _tmp31 * _tmp51 + _tmp40 * _tmp53;
|
||||
}
|
||||
} // NOLINT(readability/fn_size)
|
||||
|
||||
// NOLINTNEXTLINE(readability/fn_size)
|
||||
} // namespace sym
|
||||
|
|
@ -1,101 +0,0 @@
|
|||
// -----------------------------------------------------------------------------
|
||||
// This file was autogenerated by symforce from template:
|
||||
// function/FUNCTION.h.jinja
|
||||
// Do NOT modify by hand.
|
||||
// -----------------------------------------------------------------------------
|
||||
|
||||
#pragma once
|
||||
|
||||
#include <matrix/math.hpp>
|
||||
|
||||
namespace sym {
|
||||
|
||||
/**
|
||||
* This function was autogenerated from a symbolic function. Do not modify by hand.
|
||||
*
|
||||
* Symbolic function: yaw_var_to_lower_triangular_quat_cov
|
||||
*
|
||||
* Args:
|
||||
* state: Matrix24_1
|
||||
* yaw_var: Scalar
|
||||
*
|
||||
* Outputs:
|
||||
* q_cov_lower_triangle: Matrix44
|
||||
*/
|
||||
template <typename Scalar>
|
||||
void YawVarToLowerTriangularQuatCov(
|
||||
const matrix::Matrix<Scalar, 24, 1>& state, const Scalar yaw_var,
|
||||
matrix::Matrix<Scalar, 4, 4>* const q_cov_lower_triangle = nullptr) {
|
||||
// Total ops: 136
|
||||
|
||||
// Input arrays
|
||||
|
||||
// Intermediate terms (39)
|
||||
const Scalar _tmp0 = (Scalar(1) / Scalar(2)) * state(3, 0);
|
||||
const Scalar _tmp1 =
|
||||
-2 * std::pow(state(1, 0), Scalar(2)) - 2 * std::pow(state(2, 0), Scalar(2)) + 1;
|
||||
const Scalar _tmp2 = std::pow(_tmp1, Scalar(2)) * yaw_var;
|
||||
const Scalar _tmp3 = (Scalar(1) / Scalar(2)) * state(1, 0);
|
||||
const Scalar _tmp4 = 2 * state(2, 0);
|
||||
const Scalar _tmp5 = 2 * state(1, 0);
|
||||
const Scalar _tmp6 = -_tmp4 * state(0, 0) + _tmp5 * state(3, 0);
|
||||
const Scalar _tmp7 = _tmp1 * _tmp6 * yaw_var;
|
||||
const Scalar _tmp8 = -_tmp3 * _tmp7;
|
||||
const Scalar _tmp9 = (Scalar(1) / Scalar(2)) * state(2, 0);
|
||||
const Scalar _tmp10 = _tmp4 * state(3, 0) + _tmp5 * state(0, 0);
|
||||
const Scalar _tmp11 = _tmp10 * yaw_var;
|
||||
const Scalar _tmp12 = _tmp1 * _tmp11;
|
||||
const Scalar _tmp13 = _tmp12 * _tmp9;
|
||||
const Scalar _tmp14 = std::pow(_tmp10, Scalar(2)) * yaw_var;
|
||||
const Scalar _tmp15 = _tmp11 * _tmp6;
|
||||
const Scalar _tmp16 = _tmp15 * _tmp3;
|
||||
const Scalar _tmp17 = -_tmp0 * _tmp12;
|
||||
const Scalar _tmp18 = std::pow(_tmp6, Scalar(2)) * yaw_var;
|
||||
const Scalar _tmp19 = _tmp0 * _tmp7;
|
||||
const Scalar _tmp20 = -_tmp15 * _tmp9;
|
||||
const Scalar _tmp21 = (Scalar(1) / Scalar(2)) * state(0, 0);
|
||||
const Scalar _tmp22 = _tmp21 * _tmp7;
|
||||
const Scalar _tmp23 = _tmp17 + _tmp2 * _tmp9 + _tmp22;
|
||||
const Scalar _tmp24 = _tmp15 * _tmp21;
|
||||
const Scalar _tmp25 = -_tmp0 * _tmp14 + _tmp13 + _tmp24;
|
||||
const Scalar _tmp26 = _tmp7 * _tmp9;
|
||||
const Scalar _tmp27 = _tmp0 * _tmp15;
|
||||
const Scalar _tmp28 = _tmp18 * _tmp21 + _tmp26 - _tmp27;
|
||||
const Scalar _tmp29 = _tmp12 * _tmp21;
|
||||
const Scalar _tmp30 = _tmp19 - _tmp2 * _tmp3 + _tmp29;
|
||||
const Scalar _tmp31 = _tmp12 * _tmp3;
|
||||
const Scalar _tmp32 = _tmp14 * _tmp21 + _tmp27 - _tmp31;
|
||||
const Scalar _tmp33 = _tmp0 * _tmp18 + _tmp24 + _tmp8;
|
||||
const Scalar _tmp34 = _tmp2 * _tmp21 - _tmp26 + _tmp31;
|
||||
const Scalar _tmp35 = _tmp14 * _tmp3 + _tmp20 + _tmp29;
|
||||
const Scalar _tmp36 = (Scalar(1) / Scalar(2)) * _tmp35;
|
||||
const Scalar _tmp37 = _tmp16 - _tmp18 * _tmp9 + _tmp22;
|
||||
const Scalar _tmp38 = (Scalar(1) / Scalar(2)) * _tmp34;
|
||||
|
||||
// Output terms (1)
|
||||
if (q_cov_lower_triangle != nullptr) {
|
||||
matrix::Matrix<Scalar, 4, 4>& _q_cov_lower_triangle = (*q_cov_lower_triangle);
|
||||
|
||||
_q_cov_lower_triangle(0, 0) = -_tmp0 * (-_tmp0 * _tmp2 - _tmp13 + _tmp8) -
|
||||
_tmp3 * (-_tmp18 * _tmp3 - _tmp19 + _tmp20) -
|
||||
_tmp9 * (-_tmp14 * _tmp9 - _tmp16 + _tmp17);
|
||||
_q_cov_lower_triangle(1, 0) = -_tmp0 * _tmp23 - _tmp25 * _tmp9 - _tmp28 * _tmp3;
|
||||
_q_cov_lower_triangle(2, 0) = -_tmp0 * _tmp30 - _tmp3 * _tmp33 - _tmp32 * _tmp9;
|
||||
_q_cov_lower_triangle(3, 0) = -_tmp0 * _tmp34 - _tmp3 * _tmp37 - _tmp36 * state(2, 0);
|
||||
_q_cov_lower_triangle(0, 1) = 0;
|
||||
_q_cov_lower_triangle(1, 1) = -_tmp0 * _tmp25 + _tmp21 * _tmp28 + _tmp23 * _tmp9;
|
||||
_q_cov_lower_triangle(2, 1) = -_tmp0 * _tmp32 + _tmp21 * _tmp33 + _tmp30 * _tmp9;
|
||||
_q_cov_lower_triangle(3, 1) = -_tmp0 * _tmp35 + _tmp21 * _tmp37 + _tmp34 * _tmp9;
|
||||
_q_cov_lower_triangle(0, 2) = 0;
|
||||
_q_cov_lower_triangle(1, 2) = 0;
|
||||
_q_cov_lower_triangle(2, 2) = _tmp0 * _tmp33 + _tmp21 * _tmp32 - _tmp3 * _tmp30;
|
||||
_q_cov_lower_triangle(3, 2) = _tmp0 * _tmp37 + _tmp36 * state(0, 0) - _tmp38 * state(1, 0);
|
||||
_q_cov_lower_triangle(0, 3) = 0;
|
||||
_q_cov_lower_triangle(1, 3) = 0;
|
||||
_q_cov_lower_triangle(2, 3) = 0;
|
||||
_q_cov_lower_triangle(3, 3) = _tmp36 * state(1, 0) - _tmp37 * _tmp9 + _tmp38 * state(0, 0);
|
||||
}
|
||||
} // NOLINT(readability/fn_size)
|
||||
|
||||
// NOLINTNEXTLINE(readability/fn_size)
|
||||
} // namespace sym
|
||||
|
|
@ -36,7 +36,7 @@
|
|||
#include "test_helper/comparison_helper.h"
|
||||
|
||||
#include "../EKF/python/ekf_derivation/generated/quat_var_to_rot_var.h"
|
||||
#include "../EKF/python/ekf_derivation/generated/yaw_var_to_lower_triangular_quat_cov.h"
|
||||
#include "../EKF/python/ekf_derivation/generated/rot_var_ned_to_lower_triangular_quat_cov.h"
|
||||
#include "../EKF/python/ekf_derivation/generated/compute_yaw_321_innov_var_and_h.h"
|
||||
#include "../EKF/python/ekf_derivation/generated/compute_yaw_312_innov_var_and_h.h"
|
||||
|
||||
|
|
@ -137,11 +137,19 @@ TEST(AttitudeVariance, matlabVsSymforceZeroTilt)
|
|||
void increaseYawVar(const Vector24f &state_vector, SquareMatrix24f &P, const float yaw_var)
|
||||
{
|
||||
SquareMatrix<float, 4> q_cov;
|
||||
sym::YawVarToLowerTriangularQuatCov(state_vector, yaw_var, &q_cov);
|
||||
sym::RotVarNedToLowerTriangularQuatCov(state_vector, Vector3f(0.f, 0.f, yaw_var), &q_cov);
|
||||
q_cov.copyLowerToUpperTriangle();
|
||||
P.slice<4, 4>(0, 0) += q_cov;
|
||||
}
|
||||
|
||||
void setTiltVar(const Vector24f &state_vector, SquareMatrix24f &P, const float tilt_var)
|
||||
{
|
||||
SquareMatrix<float, 4> q_cov;
|
||||
sym::RotVarNedToLowerTriangularQuatCov(state_vector, Vector3f(tilt_var, tilt_var, 0.f), &q_cov);
|
||||
q_cov.copyLowerToUpperTriangle();
|
||||
P.slice<4, 4>(0, 0) = q_cov;
|
||||
}
|
||||
|
||||
float getYawVar(const Vector24f &state_vector, const SquareMatrix24f &P)
|
||||
{
|
||||
Vector24f H_YAW;
|
||||
|
|
@ -210,3 +218,55 @@ TEST(AttitudeVariance, increaseYawWithTilt)
|
|||
const float var_2 = getYawVar(state_vector, P);
|
||||
EXPECT_NEAR(var_2, yaw_var_1 + yaw_var_2, 1e-6f);
|
||||
}
|
||||
|
||||
TEST(AttitudeVariance, setRotVarNoTilt)
|
||||
{
|
||||
Quatf q;
|
||||
SquareMatrix24f P;
|
||||
Vector24f state_vector{};
|
||||
state_vector(0) = q(0);
|
||||
state_vector(1) = q(1);
|
||||
state_vector(2) = q(2);
|
||||
state_vector(3) = q(3);
|
||||
|
||||
const float tilt_var = radians(1.2f);
|
||||
setTiltVar(state_vector, P, tilt_var);
|
||||
|
||||
Vector3f rot_var;
|
||||
sym::QuatVarToRotVar(state_vector, P, FLT_EPSILON, &rot_var);
|
||||
|
||||
EXPECT_NEAR(rot_var(0), tilt_var, 1e-6f);
|
||||
EXPECT_NEAR(rot_var(1), tilt_var, 1e-6f);
|
||||
EXPECT_EQ(rot_var(2), 0.f);
|
||||
|
||||
// Compare against known values (special case)
|
||||
EXPECT_EQ(P(0, 0), 0.f);
|
||||
EXPECT_EQ(P(1, 1), 0.25f * tilt_var);
|
||||
EXPECT_EQ(P(2, 2), 0.25f * tilt_var);
|
||||
EXPECT_EQ(P(3, 3), 0.25f * 0.f); // no yaw var
|
||||
}
|
||||
|
||||
TEST(AttitudeVariance, setRotVarPitch90)
|
||||
{
|
||||
Quatf q(Eulerf(0.f, M_PI_F, 0.f));
|
||||
SquareMatrix24f P;
|
||||
Vector24f state_vector{};
|
||||
state_vector(0) = q(0);
|
||||
state_vector(1) = q(1);
|
||||
state_vector(2) = q(2);
|
||||
state_vector(3) = q(3);
|
||||
|
||||
const float tilt_var = radians(1.2f);
|
||||
setTiltVar(state_vector, P, tilt_var);
|
||||
|
||||
Vector3f rot_var;
|
||||
sym::QuatVarToRotVar(state_vector, P, FLT_EPSILON, &rot_var);
|
||||
|
||||
// TODO: FIXME, due to the nonlinearity of the quaternion parameters,
|
||||
// setting the variance and getting it back is approximate.
|
||||
// The correct way would be to keep the uncertainty as a 3D vector in the tangent plane
|
||||
// instead of converting it to the parameter space
|
||||
// EXPECT_NEAR(rot_var(0), tilt_var, 1e-6f);
|
||||
// EXPECT_NEAR(rot_var(1), tilt_var, 1e-6f);
|
||||
// EXPECT_EQ(rot_var(2), 0.f);
|
||||
}
|
||||
|
|
|
|||
Loading…
Reference in New Issue