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I tried gps_position smoothing from one of examples by adding random noise to measurement but it does not smooth it:
#define UKF_DOUBLE_PRECISION //#define real_t double #include <iostream> #include <Eigen/Core> #include <Eigen/Geometry> #include <cmath> #include "UKF/Types.h" #include "UKF/Integrator.h" #include "UKF/StateVector.h" #include "UKF/MeasurementVector.h" #include "UKF/Core.h" /* Set up state vector class. */ enum MyStateFields { Position, Velocity, Attitude, AngularVelocity }; using MyStateVector = UKF::StateVector< UKF::Field<Position, UKF::Vector<3>>, UKF::Field<Velocity, UKF::Vector<3>>, UKF::Field<Attitude, UKF::Quaternion>, UKF::Field<AngularVelocity, UKF::Vector<3>> >; namespace UKF { namespace Parameters { template <> constexpr real_t AlphaSquared<MyStateVector> = 1e-6; } /* State vector process model. One version takes body frame kinematic acceleration and angular acceleration as inputs, the other doesn't (assumes zero accelerations). */ template <> template <> MyStateVector MyStateVector::derivative<UKF::Vector<3>, UKF::Vector<3>>( const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) const { MyStateVector temp; /* Position derivative. */ temp.set_field<Position>(get_field<Velocity>()); /* Velocity derivative. */ temp.set_field<Velocity>(get_field<Attitude>().conjugate() * acceleration); /* Attitude derivative. */ UKF::Quaternion temp_q; temp_q.vec() = get_field<AngularVelocity>(); temp_q.w() = 0; temp.set_field<Attitude>(temp_q); /* Angular velocity derivative. */ temp.set_field<AngularVelocity>(angular_acceleration); return temp; } template <> template <> MyStateVector MyStateVector::derivative<>() const { return derivative(UKF::Vector<3>(0, 0, 0), UKF::Vector<3>(0, 0, 0)); } } /* Set up measurement vector class. */ enum MyMeasurementFields { GPS_Position, GPS_Velocity, Accelerometer, Magnetometer, Gyroscope }; using MyMeasurementVector = UKF::DynamicMeasurementVector< UKF::Field<GPS_Position, UKF::Vector<3>>, UKF::Field<GPS_Velocity, UKF::Vector<3>>, UKF::Field<Accelerometer, UKF::Vector<3>>, UKF::Field<Magnetometer, UKF::FieldVector>, UKF::Field<Gyroscope, UKF::Vector<3>> >; using MyCore = UKF::Core< MyStateVector, MyMeasurementVector, UKF::IntegratorRK4 >; namespace UKF { /* Define measurement model to be used in tests. NOTE: These are just for testing, don't expect them to make any physical sense whatsoever. */ template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, GPS_Position>(const MyStateVector& state) { return state.get_field<Position>(); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, GPS_Velocity>(const MyStateVector& state) { return state.get_field<Velocity>(); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, Accelerometer>(const MyStateVector& state) { return state.get_field<Attitude>() * UKF::Vector<3>(0, 0, -9.8); } template <> template <> UKF::FieldVector MyMeasurementVector::expected_measurement <MyStateVector, Magnetometer>(const MyStateVector& state) { return state.get_field<Attitude>() * UKF::FieldVector(1, 0, 0); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, Gyroscope>(const MyStateVector& state) { return state.get_field<AngularVelocity>(); } /* These versions of the predicted measurement functions take kinematic acceleration and angular acceleration as inputs. Note that in reality, the inputs would probably be a control vector and the accelerations would be calculated using the state vector and a dynamics model. */ template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, GPS_Position>(const MyStateVector& state, const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) { return state.get_field<Position>(); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, GPS_Velocity>(const MyStateVector& state, const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) { return state.get_field<Velocity>(); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, Accelerometer, UKF::Vector<3>>(const MyStateVector& state, const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) { return state.get_field<Attitude>() * UKF::Vector<3>(0, 0, -9.8) + acceleration; } template <> template <> UKF::FieldVector MyMeasurementVector::expected_measurement <MyStateVector, Magnetometer, UKF::Vector<3>>(const MyStateVector& state, const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) { return state.get_field<Attitude>() * UKF::FieldVector(1, 0, 0); } template <> template <> UKF::Vector<3> MyMeasurementVector::expected_measurement <MyStateVector, Gyroscope, UKF::Vector<3>>(const MyStateVector& state, const UKF::Vector<3>& acceleration, const UKF::Vector<3>& angular_acceleration) { return state.get_field<AngularVelocity>(); } } MyCore create_initialised_test_filter() { MyCore test_filter; test_filter.state.set_field<Position>(UKF::Vector<3>(0, 0, 0)); test_filter.state.set_field<Velocity>(UKF::Vector<3>(0, 0, 0)); test_filter.state.set_field<Attitude>(UKF::Quaternion(1, 0, 0, 0)); test_filter.state.set_field<AngularVelocity>(UKF::Vector<3>(0, 0, 0)); test_filter.covariance = MyStateVector::CovarianceMatrix::Zero(); test_filter.covariance.diagonal() << 10000, 10000, 10000, 100, 100, 100, 1, 1, 5, 10, 10, 10; test_filter.measurement_covariance << 10, 10, 10, 1, 1, 1, 5e-1, 5e-1, 5e-1, 5e-1, 5e-1, 5e-1, 0.05, 0.05, 0.05; real_t a, b; real_t dt = 0.01; a = std::sqrt(0.1 * dt * dt); b = std::sqrt(0.1 * dt); test_filter.process_noise_covariance << a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, a, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, b; return test_filter; } #include <random> static std::random_device rd; // random device engine, usually based on /dev/random on UNIX-like systems // initialize Mersennes' twister using rd to generate the seed static std::mt19937 rng{ rd() }; double dice() { static std::uniform_real_distribution<double> uid(-5, 5); // random dice return uid(rng); // use rng as a generator } int main() { MyCore test_filter = create_initialised_test_filter(); MyMeasurementVector m; m.set_field<GPS_Position>(UKF::Vector<3>(100, 10, -50)); m.set_field<GPS_Velocity>(UKF::Vector<3>(20, 0, 0)); m.set_field<Accelerometer>(UKF::Vector<3>(0, 0, -14.8)); m.set_field<Magnetometer>(UKF::FieldVector(0, -1, 0)); m.set_field<Gyroscope>(UKF::Vector<3>(0.5, 0, 0)); for (int i = 0; i < 100; i++) { // gps position: 100 +/- 5, 10, -50 measured m.set_field<GPS_Position>(UKF::Vector<3>(100+dice(), 10, -50)); test_filter.step(0.01, m, UKF::Vector<3>(0, 0, -5), UKF::Vector<3>(1, 0, 0)); // does not smooth std::cout << m.get_field<Position>() << std::endl; std::cout << "-------------" << std::endl; } return 0; }
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I tried gps_position smoothing from one of examples by adding random noise to measurement but it does not smooth it:
The text was updated successfully, but these errors were encountered: