/* ---------------------------------------------------------------------------- * GTSAM Copyright 2010, Georgia Tech Research Corporation, * Atlanta, Georgia 30332-0415 * All Rights Reserved * Authors: Frank Dellaert, et al. (see THANKS for the full author list) * See LICENSE for the license information * -------------------------------------------------------------------------- */ /** * @file InertialNavFactor_GlobalVelocity.h * @author Vadim Indelman, Stephen Williams * @brief Inertial navigation factor (velocity in the global frame) * @date Sept 13, 2012 **/ #pragma once #include #include #include #include // Using numerical derivative to calculate d(Pose3::Expmap)/dw #include #include #include #include namespace gtsam { /* * NOTES: * ===== * - The global frame (NED or ENU) is defined by the user by specifying the gravity vector in this frame. * - The IMU frame is implicitly defined by the user via the rotation matrix between global and imu frames. * - Camera and IMU frames are identical * - The user should specify a continuous equivalent noise covariance, which can be calculated using * the static function CalcEquivalentNoiseCov based on the IMU gyro and acc measurement noise covariance * matrices and the process\modeling covariance matrix. The IneritalNavFactor converts this into a * discrete form using the supplied delta_t between sub-sequential measurements. * - Earth-rate correction: * + Currently the user should supply R_ECEF_to_G, which is the rotation from ECEF to the global * frame (Local-Level system: ENU or NED, see above). * + R_ECEF_to_G can be calculated by approximated values of latitude and longitude of the system. * + Currently it is assumed that a relatively small distance is traveled w.r.t. to initial pose, since R_ECEF_to_G is constant. * Otherwise, R_ECEF_to_G should be updated each time using the current lat-lon. * * - Frame Notation: * Quantities are written as {Frame of Representation/Destination Frame}_{Quantity Type}_{Quatity Description/Origination Frame} * So, the rotational velocity of the sensor written in the body frame is: body_omega_sensor * And the transformation from the body frame to the world frame would be: world_P_body * This allows visual chaining. For example, converting the sensed angular velocity of the IMU * (angular velocity of the sensor in the sensor frame) into the world frame can be performed as: * world_R_body * body_R_sensor * sensor_omega_sensor = world_omega_sensor * * * - Common Quantity Types * P : pose/3d transformation * R : rotation * omega : angular velocity * t : translation * v : velocity * a : acceleration * * - Common Frames * sensor : the coordinate system attached to the sensor origin * body : the coordinate system attached to body/inertial frame. * Unless an optional frame transformation is provided, the * sensor frame and the body frame will be identical * world : the global/world coordinate frame. This is assumed to be * a tangent plane to the earth's surface somewhere near the * vehicle */ template class InertialNavFactor_GlobalVelocity : public NoiseModelFactor5 { private: typedef InertialNavFactor_GlobalVelocity This; typedef NoiseModelFactor5 Base; Vector measurement_acc_; Vector measurement_gyro_; double dt_; Vector world_g_; Vector world_rho_; Vector world_omega_earth_; boost::optional body_P_sensor_; // The pose of the sensor in the body frame public: // shorthand for a smart pointer to a factor typedef typename boost::shared_ptr shared_ptr; /** default constructor - only use for serialization */ InertialNavFactor_GlobalVelocity() {} /** Constructor */ InertialNavFactor_GlobalVelocity(const Key& Pose1, const Key& Vel1, const Key& IMUBias1, const Key& Pose2, const Key& Vel2, const Vector& measurement_acc, const Vector& measurement_gyro, const double measurement_dt, const Vector world_g, const Vector world_rho, const Vector& world_omega_earth, const noiseModel::Gaussian::shared_ptr& model_continuous, boost::optional body_P_sensor = boost::none) : Base(calc_descrete_noise_model(model_continuous, measurement_dt ), Pose1, Vel1, IMUBias1, Pose2, Vel2), measurement_acc_(measurement_acc), measurement_gyro_(measurement_gyro), dt_(measurement_dt), world_g_(world_g), world_rho_(world_rho), world_omega_earth_(world_omega_earth), body_P_sensor_(body_P_sensor) { } ~InertialNavFactor_GlobalVelocity() override {} /** implement functions needed for Testable */ /** print */ void print(const std::string& s = "InertialNavFactor_GlobalVelocity", const KeyFormatter& keyFormatter = DefaultKeyFormatter) const override { std::cout << s << "(" << keyFormatter(this->key1()) << "," << keyFormatter(this->key2()) << "," << keyFormatter(this->key3()) << "," << keyFormatter(this->key4()) << "," << keyFormatter(this->key5()) << "\n"; std::cout << "acc measurement: " << this->measurement_acc_.transpose() << std::endl; std::cout << "gyro measurement: " << this->measurement_gyro_.transpose() << std::endl; std::cout << "dt: " << this->dt_ << std::endl; std::cout << "gravity (in world frame): " << this->world_g_.transpose() << std::endl; std::cout << "craft rate (in world frame): " << this->world_rho_.transpose() << std::endl; std::cout << "earth's rotation (in world frame): " << this->world_omega_earth_.transpose() << std::endl; if(this->body_P_sensor_) this->body_P_sensor_->print(" sensor pose in body frame: "); this->noiseModel_->print(" noise model"); } /** equals */ bool equals(const NonlinearFactor& expected, double tol=1e-9) const override { const This *e = dynamic_cast (&expected); return e != nullptr && Base::equals(*e, tol) && (measurement_acc_ - e->measurement_acc_).norm() < tol && (measurement_gyro_ - e->measurement_gyro_).norm() < tol && (dt_ - e->dt_) < tol && (world_g_ - e->world_g_).norm() < tol && (world_rho_ - e->world_rho_).norm() < tol && (world_omega_earth_ - e->world_omega_earth_).norm() < tol && ((!body_P_sensor_ && !e->body_P_sensor_) || (body_P_sensor_ && e->body_P_sensor_ && body_P_sensor_->equals(*e->body_P_sensor_))); } POSE predictPose(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1) const { // Calculate the corrected measurements using the Bias object Vector GyroCorrected(Bias1.correctGyroscope(measurement_gyro_)); const POSE& world_P1_body = Pose1; const VELOCITY& world_V1_body = Vel1; // Calculate the acceleration and angular velocity of the body in the body frame (including earth-related rotations) Vector body_omega_body; if(body_P_sensor_) { body_omega_body = body_P_sensor_->rotation().matrix() * GyroCorrected; } else { body_omega_body = GyroCorrected; } // Convert earth-related terms into the body frame Matrix body_R_world(world_P1_body.rotation().inverse().matrix()); Vector body_rho = body_R_world * world_rho_; Vector body_omega_earth = body_R_world * world_omega_earth_; // Correct for earth-related terms body_omega_body -= body_rho + body_omega_earth; // The velocity is in the global frame, so composing Pose1 with v*dt is incorrect return POSE(Pose1.rotation() * POSE::Rotation::Expmap(body_omega_body*dt_), Pose1.translation() + typename POSE::Translation(world_V1_body*dt_)); } VELOCITY predictVelocity(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1) const { // Calculate the corrected measurements using the Bias object Vector AccCorrected(Bias1.correctAccelerometer(measurement_acc_)); const POSE& world_P1_body = Pose1; const VELOCITY& world_V1_body = Vel1; // Calculate the acceleration and angular velocity of the body in the body frame (including earth-related rotations) Vector body_a_body, body_omega_body; if(body_P_sensor_) { Matrix body_R_sensor = body_P_sensor_->rotation().matrix(); Vector GyroCorrected(Bias1.correctGyroscope(measurement_gyro_)); body_omega_body = body_R_sensor * GyroCorrected; Matrix body_omega_body__cross = skewSymmetric(body_omega_body); body_a_body = body_R_sensor * AccCorrected - body_omega_body__cross * body_omega_body__cross * body_P_sensor_->translation(); } else { body_a_body = AccCorrected; } // Correct for earth-related terms Vector world_a_body = world_P1_body.rotation().matrix() * body_a_body + world_g_ - 2*skewSymmetric(world_rho_ + world_omega_earth_)*world_V1_body; // Calculate delta in the body frame VELOCITY VelDelta(world_a_body*dt_); // Predict return Vel1 + VelDelta; } void predict(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1, POSE& Pose2, VELOCITY& Vel2) const { Pose2 = predictPose(Pose1, Vel1, Bias1); Vel2 = predictVelocity(Pose1, Vel1, Bias1); } POSE evaluatePoseError(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1, const POSE& Pose2, const VELOCITY& Vel2) const { // Predict POSE Pose2Pred = predictPose(Pose1, Vel1, Bias1); // Calculate error return Pose2.between(Pose2Pred); } VELOCITY evaluateVelocityError(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1, const POSE& Pose2, const VELOCITY& Vel2) const { // Predict VELOCITY Vel2Pred = predictVelocity(Pose1, Vel1, Bias1); // Calculate error return Vel2Pred - Vel2; } /** implement functions needed to derive from Factor */ Vector evaluateError(const POSE& Pose1, const VELOCITY& Vel1, const IMUBIAS& Bias1, const POSE& Pose2, const VELOCITY& Vel2, boost::optional H1 = boost::none, boost::optional H2 = boost::none, boost::optional H3 = boost::none, boost::optional H4 = boost::none, boost::optional H5 = boost::none) const override { // TODO: Write analytical derivative calculations // Jacobian w.r.t. Pose1 if (H1){ Matrix H1_Pose = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluatePoseError, this, std::placeholders::_1, Vel1, Bias1, Pose2, Vel2), Pose1); Matrix H1_Vel = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluateVelocityError, this, std::placeholders::_1, Vel1, Bias1, Pose2, Vel2), Pose1); *H1 = stack(2, &H1_Pose, &H1_Vel); } // Jacobian w.r.t. Vel1 if (H2){ if (Vel1.size()!=3) throw std::runtime_error("Frank's hack to make this compile will not work if size != 3"); Matrix H2_Pose = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluatePoseError, this, Pose1, std::placeholders::_1, Bias1, Pose2, Vel2), Vel1); Matrix H2_Vel = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluateVelocityError, this, Pose1, std::placeholders::_1, Bias1, Pose2, Vel2), Vel1); *H2 = stack(2, &H2_Pose, &H2_Vel); } // Jacobian w.r.t. IMUBias1 if (H3){ Matrix H3_Pose = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluatePoseError, this, Pose1, Vel1, std::placeholders::_1, Pose2, Vel2), Bias1); Matrix H3_Vel = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluateVelocityError, this, Pose1, Vel1, std::placeholders::_1, Pose2, Vel2), Bias1); *H3 = stack(2, &H3_Pose, &H3_Vel); } // Jacobian w.r.t. Pose2 if (H4){ Matrix H4_Pose = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluatePoseError, this, Pose1, Vel1, Bias1, std::placeholders::_1, Vel2), Pose2); Matrix H4_Vel = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluateVelocityError, this, Pose1, Vel1, Bias1, std::placeholders::_1, Vel2), Pose2); *H4 = stack(2, &H4_Pose, &H4_Vel); } // Jacobian w.r.t. Vel2 if (H5){ if (Vel2.size()!=3) throw std::runtime_error("Frank's hack to make this compile will not work if size != 3"); Matrix H5_Pose = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluatePoseError, this, Pose1, Vel1, Bias1, Pose2, std::placeholders::_1), Vel2); Matrix H5_Vel = gtsam::numericalDerivative11( std::bind(&InertialNavFactor_GlobalVelocity::evaluateVelocityError, this, Pose1, Vel1, Bias1, Pose2, std::placeholders::_1), Vel2); *H5 = stack(2, &H5_Pose, &H5_Vel); } Vector ErrPoseVector(POSE::Logmap(evaluatePoseError(Pose1, Vel1, Bias1, Pose2, Vel2))); Vector ErrVelVector(evaluateVelocityError(Pose1, Vel1, Bias1, Pose2, Vel2)); return concatVectors(2, &ErrPoseVector, &ErrVelVector); } static inline noiseModel::Gaussian::shared_ptr CalcEquivalentNoiseCov(const noiseModel::Gaussian::shared_ptr& gaussian_acc, const noiseModel::Gaussian::shared_ptr& gaussian_gyro, const noiseModel::Gaussian::shared_ptr& gaussian_process){ Matrix cov_acc = ( gaussian_acc->R().transpose() * gaussian_acc->R() ).inverse(); Matrix cov_gyro = ( gaussian_gyro->R().transpose() * gaussian_gyro->R() ).inverse(); Matrix cov_process = ( gaussian_process->R().transpose() * gaussian_process->R() ).inverse(); cov_process.block(0,0, 3,3) += cov_gyro; cov_process.block(6,6, 3,3) += cov_acc; return noiseModel::Gaussian::Covariance(cov_process); } static inline void Calc_g_rho_omega_earth_NED(const Vector& Pos_NED, const Vector& Vel_NED, const Vector& LatLonHeight_IC, const Vector& Pos_NED_Initial, Vector& g_NED, Vector& rho_NED, Vector& omega_earth_NED) { Matrix ENU_to_NED = (Matrix(3, 3) << 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0).finished(); Matrix NED_to_ENU = (Matrix(3, 3) << 0.0, 1.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, -1.0).finished(); // Convert incoming parameters to ENU Vector Pos_ENU = NED_to_ENU * Pos_NED; Vector Vel_ENU = NED_to_ENU * Vel_NED; Vector Pos_ENU_Initial = NED_to_ENU * Pos_NED_Initial; // Call ENU version Vector g_ENU; Vector rho_ENU; Vector omega_earth_ENU; Calc_g_rho_omega_earth_ENU(Pos_ENU, Vel_ENU, LatLonHeight_IC, Pos_ENU_Initial, g_ENU, rho_ENU, omega_earth_ENU); // Convert output to NED g_NED = ENU_to_NED * g_ENU; rho_NED = ENU_to_NED * rho_ENU; omega_earth_NED = ENU_to_NED * omega_earth_ENU; } static inline void Calc_g_rho_omega_earth_ENU(const Vector& Pos_ENU, const Vector& Vel_ENU, const Vector& LatLonHeight_IC, const Vector& Pos_ENU_Initial, Vector& g_ENU, Vector& rho_ENU, Vector& omega_earth_ENU){ double R0 = 6.378388e6; double e = 1/297; double Re( R0*( 1-e*(sin( LatLonHeight_IC(0) ))*(sin( LatLonHeight_IC(0) )) ) ); // Calculate current lat, lon Vector delta_Pos_ENU(Pos_ENU - Pos_ENU_Initial); double delta_lat(delta_Pos_ENU(1)/Re); double delta_lon(delta_Pos_ENU(0)/(Re*cos(LatLonHeight_IC(0)))); double lat_new(LatLonHeight_IC(0) + delta_lat); double lon_new(LatLonHeight_IC(1) + delta_lon); // Rotation of lon about z axis Rot3 C1(cos(lon_new), sin(lon_new), 0.0, -sin(lon_new), cos(lon_new), 0.0, 0.0, 0.0, 1.0); // Rotation of lat about y axis Rot3 C2(cos(lat_new), 0.0, sin(lat_new), 0.0, 1.0, 0.0, -sin(lat_new), 0.0, cos(lat_new)); Rot3 UEN_to_ENU(0, 1, 0, 0, 0, 1, 1, 0, 0); Rot3 R_ECEF_to_ENU( UEN_to_ENU * C2 * C1 ); Vector omega_earth_ECEF(Vector3(0.0, 0.0, 7.292115e-5)); omega_earth_ENU = R_ECEF_to_ENU.matrix() * omega_earth_ECEF; // Calculating g double height(LatLonHeight_IC(2)); double EQUA_RADIUS = 6378137.0; // equatorial radius of the earth; WGS-84 double ECCENTRICITY = 0.0818191908426; // eccentricity of the earth ellipsoid double e2( pow(ECCENTRICITY,2) ); double den( 1-e2*pow(sin(lat_new),2) ); double Rm( (EQUA_RADIUS*(1-e2))/( pow(den,(3/2)) ) ); double Rp( EQUA_RADIUS/( sqrt(den) ) ); double Ro( sqrt(Rp*Rm) ); // mean earth radius of curvature double g0( 9.780318*( 1 + 5.3024e-3 * pow(sin(lat_new),2) - 5.9e-6 * pow(sin(2*lat_new),2) ) ); double g_calc( g0/( pow(1 + height/Ro, 2) ) ); g_ENU = (Vector(3) << 0.0, 0.0, -g_calc).finished(); // Calculate rho double Ve( Vel_ENU(0) ); double Vn( Vel_ENU(1) ); double rho_E = -Vn/(Rm + height); double rho_N = Ve/(Rp + height); double rho_U = Ve*tan(lat_new)/(Rp + height); rho_ENU = (Vector(3) << rho_E, rho_N, rho_U).finished(); } static inline noiseModel::Gaussian::shared_ptr calc_descrete_noise_model(const noiseModel::Gaussian::shared_ptr& model, double delta_t){ /* Q_d (approx)= Q * delta_t */ /* In practice, square root of the information matrix is represented, so that: * R_d (approx)= R / sqrt(delta_t) * */ return noiseModel::Gaussian::SqrtInformation(model->R()/std::sqrt(delta_t)); } private: /** Serialization function */ friend class boost::serialization::access; template void serialize(ARCHIVE & ar, const unsigned int /*version*/) { ar & boost::serialization::make_nvp("NonlinearFactor2", boost::serialization::base_object(*this)); } }; // \class InertialNavFactor_GlobalVelocity /// traits template struct traits > : public Testable > { }; } /// namespace aspn