277 lines
12 KiB
C++
277 lines
12 KiB
C++
/* ----------------------------------------------------------------------------
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* GTSAM Copyright 2010, Georgia Tech Research Corporation,
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* Atlanta, Georgia 30332-0415
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* All Rights Reserved
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* Authors: Frank Dellaert, et al. (see THANKS for the full author list)
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* See LICENSE for the license information
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* -------------------------------------------------------------------------- */
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/**
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* @file CombinedImuFactor.cpp
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* @author Luca Carlone
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* @author Stephen Williams
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* @author Richard Roberts
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* @author Vadim Indelman
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* @author David Jensen
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* @author Frank Dellaert
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**/
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#include <gtsam/navigation/CombinedImuFactor.h>
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/* External or standard includes */
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#include <ostream>
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namespace gtsam {
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using namespace std;
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//------------------------------------------------------------------------------
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// Inner class CombinedPreintegratedMeasurements
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//------------------------------------------------------------------------------
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CombinedImuFactor::CombinedPreintegratedMeasurements::CombinedPreintegratedMeasurements(
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const imuBias::ConstantBias& bias, const Matrix3& measuredAccCovariance,
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const Matrix3& measuredOmegaCovariance,
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const Matrix3& integrationErrorCovariance, const Matrix3& biasAccCovariance,
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const Matrix3& biasOmegaCovariance, const Matrix& biasAccOmegaInit,
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const bool use2ndOrderIntegration) :
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PreintegrationBase(bias, measuredAccCovariance, measuredOmegaCovariance,
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integrationErrorCovariance, use2ndOrderIntegration), biasAccCovariance_(
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biasAccCovariance), biasOmegaCovariance_(biasOmegaCovariance), biasAccOmegaInit_(
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biasAccOmegaInit) {
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preintMeasCov_.setZero();
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}
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//------------------------------------------------------------------------------
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void CombinedImuFactor::CombinedPreintegratedMeasurements::print(
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const string& s) const {
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PreintegrationBase::print(s);
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cout << " biasAccCovariance [ " << biasAccCovariance_ << " ]" << endl;
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cout << " biasOmegaCovariance [ " << biasOmegaCovariance_ << " ]" << endl;
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cout << " biasAccOmegaInit [ " << biasAccOmegaInit_ << " ]" << endl;
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cout << " preintMeasCov [ " << preintMeasCov_ << " ]" << endl;
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}
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//------------------------------------------------------------------------------
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bool CombinedImuFactor::CombinedPreintegratedMeasurements::equals(
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const CombinedPreintegratedMeasurements& expected, double tol) const {
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return equal_with_abs_tol(biasAccCovariance_, expected.biasAccCovariance_,
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tol)
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&& equal_with_abs_tol(biasOmegaCovariance_, expected.biasOmegaCovariance_,
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tol)
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&& equal_with_abs_tol(biasAccOmegaInit_, expected.biasAccOmegaInit_, tol)
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&& equal_with_abs_tol(preintMeasCov_, expected.preintMeasCov_, tol)
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&& PreintegrationBase::equals(expected, tol);
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}
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//------------------------------------------------------------------------------
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void CombinedImuFactor::CombinedPreintegratedMeasurements::resetIntegration() {
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PreintegrationBase::resetIntegration();
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preintMeasCov_.setZero();
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}
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//------------------------------------------------------------------------------
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void CombinedImuFactor::CombinedPreintegratedMeasurements::integrateMeasurement(
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const Vector3& measuredAcc, const Vector3& measuredOmega, double deltaT,
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boost::optional<const Pose3&> body_P_sensor,
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boost::optional<Matrix&> F_test, boost::optional<Matrix&> G_test) {
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// NOTE: order is important here because each update uses old values, e.g., velocity and position updates are based on previous rotation estimate.
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// (i.e., we have to update jacobians and covariances before updating preintegrated measurements).
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Vector3 correctedAcc, correctedOmega;
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correctMeasurementsByBiasAndSensorPose(measuredAcc, measuredOmega,
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correctedAcc, correctedOmega, body_P_sensor);
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const Vector3 integratedOmega = correctedOmega * deltaT; // rotation vector describing rotation increment computed from the current rotation rate measurement
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Matrix3 D_Rincr_integratedOmega; // Right jacobian computed at theta_incr
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const Rot3 Rincr = Rot3::Expmap(integratedOmega, D_Rincr_integratedOmega); // rotation increment computed from the current rotation rate measurement
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// Update Jacobians
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/* ----------------------------------------------------------------------------------------------------------------------- */
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updatePreintegratedJacobians(correctedAcc, D_Rincr_integratedOmega, Rincr,
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deltaT);
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// Update preintegrated measurements covariance: as in [2] we consider a first order propagation that
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// can be seen as a prediction phase in an EKF framework. In this implementation, contrarily to [2] we
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// consider the uncertainty of the bias selection and we keep correlation between biases and preintegrated measurements
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/* ----------------------------------------------------------------------------------------------------------------------- */
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const Matrix3 R_i = deltaRij(); // store this
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// Update preintegrated measurements. TODO Frank moved from end of this function !!!
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Matrix9 F_9x9;
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updatePreintegratedMeasurements(correctedAcc, Rincr, deltaT, F_9x9);
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// Single Jacobians to propagate covariance
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Matrix3 H_vel_biasacc = -R_i * deltaT;
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Matrix3 H_angles_biasomega = -D_Rincr_integratedOmega * deltaT;
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// overall Jacobian wrt preintegrated measurements (df/dx)
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Matrix F(15, 15);
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// for documentation:
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// F << I_3x3, I_3x3 * deltaT, Z_3x3, Z_3x3, Z_3x3,
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// Z_3x3, I_3x3, H_vel_angles, H_vel_biasacc, Z_3x3,
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// Z_3x3, Z_3x3, H_angles_angles, Z_3x3, H_angles_biasomega,
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// Z_3x3, Z_3x3, Z_3x3, I_3x3, Z_3x3,
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// Z_3x3, Z_3x3, Z_3x3, Z_3x3, I_3x3;
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F.setZero();
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F.block<9, 9>(0, 0) = F_9x9;
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F.block<6, 6>(9, 9) = I_6x6;
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F.block<3, 3>(3, 9) = H_vel_biasacc;
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F.block<3, 3>(6, 12) = H_angles_biasomega;
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// first order uncertainty propagation
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// Optimized matrix multiplication (1/deltaT) * G * measurementCovariance * G.transpose()
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Matrix G_measCov_Gt = Matrix::Zero(15, 15);
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// BLOCK DIAGONAL TERMS
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G_measCov_Gt.block<3, 3>(0, 0) = deltaT * integrationCovariance();
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G_measCov_Gt.block<3, 3>(3, 3) = (1 / deltaT) * (H_vel_biasacc)
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* (accelerometerCovariance() + biasAccOmegaInit_.block<3, 3>(0, 0))
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* (H_vel_biasacc.transpose());
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G_measCov_Gt.block<3, 3>(6, 6) = (1 / deltaT) * (H_angles_biasomega)
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* (gyroscopeCovariance() + biasAccOmegaInit_.block<3, 3>(3, 3))
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* (H_angles_biasomega.transpose());
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G_measCov_Gt.block<3, 3>(9, 9) = deltaT * biasAccCovariance_;
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G_measCov_Gt.block<3, 3>(12, 12) = deltaT * biasOmegaCovariance_;
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// OFF BLOCK DIAGONAL TERMS
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Matrix3 block23 = H_vel_biasacc * biasAccOmegaInit_.block<3, 3>(3, 0)
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* H_angles_biasomega.transpose();
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G_measCov_Gt.block<3, 3>(3, 6) = block23;
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G_measCov_Gt.block<3, 3>(6, 3) = block23.transpose();
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preintMeasCov_ = F * preintMeasCov_ * F.transpose() + G_measCov_Gt;
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// F_test and G_test are used for testing purposes and are not needed by the factor
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if (F_test) {
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F_test->resize(15, 15);
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(*F_test) << F;
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}
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if (G_test) {
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G_test->resize(15, 21);
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// This is for testing & documentation
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///< measurementCovariance_ : cov[integrationError measuredAcc measuredOmega biasAccRandomWalk biasOmegaRandomWalk biasAccInit biasOmegaInit] in R^(21 x 21)
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(*G_test) << //
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I_3x3 * deltaT, Z_3x3, Z_3x3, Z_3x3, Z_3x3, Z_3x3, Z_3x3, //
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Z_3x3, -H_vel_biasacc, Z_3x3, Z_3x3, Z_3x3, H_vel_biasacc, Z_3x3, //
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Z_3x3, Z_3x3, -H_angles_biasomega, Z_3x3, Z_3x3, Z_3x3, H_angles_biasomega, //
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Z_3x3, Z_3x3, Z_3x3, I_3x3, Z_3x3, Z_3x3, Z_3x3, //
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Z_3x3, Z_3x3, Z_3x3, Z_3x3, I_3x3, Z_3x3, Z_3x3;
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}
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}
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//------------------------------------------------------------------------------
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// CombinedImuFactor methods
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//------------------------------------------------------------------------------
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CombinedImuFactor::CombinedImuFactor() :
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ImuFactorBase(), _PIM_(imuBias::ConstantBias(), Z_3x3, Z_3x3, Z_3x3, Z_3x3,
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Z_3x3, Z_6x6) {
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}
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//------------------------------------------------------------------------------
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CombinedImuFactor::CombinedImuFactor(Key pose_i, Key vel_i, Key pose_j,
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Key vel_j, Key bias_i, Key bias_j,
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const CombinedPreintegratedMeasurements& preintegratedMeasurements,
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const Vector3& gravity, const Vector3& omegaCoriolis,
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boost::optional<const Pose3&> body_P_sensor, const bool use2ndOrderCoriolis) :
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Base(
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noiseModel::Gaussian::Covariance(
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preintegratedMeasurements.preintMeasCov_), pose_i, vel_i, pose_j,
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vel_j, bias_i, bias_j), ImuFactorBase(gravity, omegaCoriolis,
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body_P_sensor, use2ndOrderCoriolis), _PIM_(preintegratedMeasurements) {
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}
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//------------------------------------------------------------------------------
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gtsam::NonlinearFactor::shared_ptr CombinedImuFactor::clone() const {
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return boost::static_pointer_cast<gtsam::NonlinearFactor>(
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gtsam::NonlinearFactor::shared_ptr(new This(*this)));
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}
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//------------------------------------------------------------------------------
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void CombinedImuFactor::print(const string& s,
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const KeyFormatter& keyFormatter) const {
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cout << s << "CombinedImuFactor(" << keyFormatter(this->key1()) << ","
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<< keyFormatter(this->key2()) << "," << keyFormatter(this->key3()) << ","
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<< keyFormatter(this->key4()) << "," << keyFormatter(this->key5()) << ","
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<< keyFormatter(this->key6()) << ")\n";
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ImuFactorBase::print("");
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_PIM_.print(" preintegrated measurements:");
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this->noiseModel_->print(" noise model: ");
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}
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//------------------------------------------------------------------------------
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bool CombinedImuFactor::equals(const NonlinearFactor& expected,
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double tol) const {
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const This *e = dynamic_cast<const This*>(&expected);
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return e != NULL && Base::equals(*e, tol) && _PIM_.equals(e->_PIM_, tol)
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&& ImuFactorBase::equals(*e, tol);
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}
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//------------------------------------------------------------------------------
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Vector CombinedImuFactor::evaluateError(const Pose3& pose_i,
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const Vector3& vel_i, const Pose3& pose_j, const Vector3& vel_j,
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const imuBias::ConstantBias& bias_i, const imuBias::ConstantBias& bias_j,
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boost::optional<Matrix&> H1, boost::optional<Matrix&> H2,
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boost::optional<Matrix&> H3, boost::optional<Matrix&> H4,
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boost::optional<Matrix&> H5, boost::optional<Matrix&> H6) const {
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// error wrt bias evolution model (random walk)
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Matrix6 Hbias_i, Hbias_j;
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Vector6 fbias = traits<imuBias::ConstantBias>::Between(bias_j, bias_i,
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H6 ? &Hbias_j : 0, H5 ? &Hbias_i : 0).vector();
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Matrix96 D_r_pose_i, D_r_pose_j, D_r_bias_i;
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Matrix93 D_r_vel_i, D_r_vel_j;
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// error wrt preintegrated measurements
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Vector9 r_pvR = _PIM_.computeErrorAndJacobians(pose_i, vel_i, pose_j, vel_j,
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bias_i, gravity_, omegaCoriolis_, use2ndOrderCoriolis_,
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H1 ? &D_r_pose_i : 0, H2 ? &D_r_vel_i : 0, H3 ? &D_r_pose_j : 0,
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H4 ? &D_r_vel_j : 0, H5 ? &D_r_bias_i : 0);
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// if we need the jacobians
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if (H1) {
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H1->resize(15, 6);
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H1->block<9, 6>(0, 0) = D_r_pose_i;
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// adding: [dBiasAcc/dPi ; dBiasOmega/dPi]
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H1->block<6, 6>(9, 0) = Z_6x6;
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}
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if (H2) {
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H2->resize(15, 3);
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H2->block<9, 3>(0, 0) = D_r_vel_i;
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// adding: [dBiasAcc/dVi ; dBiasOmega/dVi]
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H2->block<6, 3>(9, 0) = Matrix::Zero(6, 3);
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}
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if (H3) {
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H3->resize(15, 6);
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H3->block<9, 6>(0, 0) = D_r_pose_j;
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// adding: [dBiasAcc/dPj ; dBiasOmega/dPj]
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H3->block<6, 6>(9, 0) = Z_6x6;
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}
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if (H4) {
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H4->resize(15, 3);
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H4->block<9, 3>(0, 0) = D_r_vel_j;
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// adding: [dBiasAcc/dVi ; dBiasOmega/dVi]
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H4->block<6, 3>(9, 0) = Matrix::Zero(6, 3);
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}
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if (H5) {
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H5->resize(15, 6);
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H5->block<9, 6>(0, 0) = D_r_bias_i;
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// adding: [dBiasAcc/dBias_i ; dBiasOmega/dBias_i]
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H5->block<6, 6>(9, 0) = Hbias_i;
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}
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if (H6) {
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H6->resize(15, 6);
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H6->block<9, 6>(0, 0) = Matrix::Zero(9, 6);
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// adding: [dBiasAcc/dBias_j ; dBiasOmega/dBias_j]
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H6->block<6, 6>(9, 0) = Hbias_j;
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}
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// overall error
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Vector r(15);
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r << r_pvR, fbias; // vector of size 15
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return r;
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}
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} /// namespace gtsam
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