CombinedImuFactor.h

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/* ----------------------------------------------------------------------------

 * 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

 * -------------------------------------------------------------------------- */

#pragma once

/* GTSAM includes */
#include <gtsam/navigation/ManifoldPreintegration.h>
#include <gtsam/navigation/TangentPreintegration.h>
#include <gtsam/nonlinear/NonlinearFactor.h>
#include <gtsam/base/Matrix.h>

namespace gtsam {

#ifdef GTSAM_TANGENT_PREINTEGRATION
typedef TangentPreintegration PreintegrationType;
#else
typedef ManifoldPreintegration PreintegrationType;
#endif

/*
 * If you are using the factor, please cite:
 * L. Carlone, Z. Kira, C. Beall, V. Indelman, F. Dellaert, Eliminating
 * conditionally independent sets in factor graphs: a unifying perspective based
 * on smart factors, Int. Conf. on Robotics and Automation (ICRA), 2014.
 *
 * REFERENCES:
 * [1] G.S. Chirikjian, "Stochastic Models, Information Theory, and Lie Groups",
 *     Volume 2, 2008.
 * [2] T. Lupton and S.Sukkarieh, "Visual-Inertial-Aided Navigation for
 *     High-Dynamic Motion in Built Environments Without Initial Conditions",
 *     TRO, 28(1):61-76, 2012.
 * [3] L. Carlone, S. Williams, R. Roberts, "Preintegrated IMU factor:
 *     Computation of the Jacobian Matrices", Tech. Report, 2013.
 * [4] C. Forster, L. Carlone, F. Dellaert, D. Scaramuzza, IMU Preintegration on
 *     Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation,
 *     Robotics: Science and Systems (RSS), 2015.
 */

class PreintegratedCombinedMeasurements : public PreintegrationType {

public:

  struct Params : PreintegrationParams {
    Matrix3 biasAccCovariance;    
    Matrix3 biasOmegaCovariance;  
    Matrix6 biasAccOmegaInt;     

    Params(const Vector3& n_gravity) :
        PreintegrationParams(n_gravity), biasAccCovariance(I_3x3), biasOmegaCovariance(
            I_3x3), biasAccOmegaInt(I_6x6) {
    }

    // Default Params for a Z-down navigation frame, such as NED: gravity points along positive Z-axis
    static boost::shared_ptr<Params> MakeSharedD(double g = 9.81) {
      return boost::shared_ptr<Params>(new Params(Vector3(0, 0, g)));
    }

    // Default Params for a Z-up navigation frame, such as ENU: gravity points along negative Z-axis
    static boost::shared_ptr<Params> MakeSharedU(double g = 9.81) {
      return boost::shared_ptr<Params>(new Params(Vector3(0, 0, -g)));
    }

   private:
    Params() {}

    friend class boost::serialization::access;
    template <class ARCHIVE>
    void serialize(ARCHIVE& ar, const unsigned int /*version*/) {
      ar& BOOST_SERIALIZATION_BASE_OBJECT_NVP(PreintegratedRotation::Params);
      ar& BOOST_SERIALIZATION_NVP(biasAccCovariance);
      ar& BOOST_SERIALIZATION_NVP(biasOmegaCovariance);
      ar& BOOST_SERIALIZATION_NVP(biasAccOmegaInt);
    }

   public:
    EIGEN_MAKE_ALIGNED_OPERATOR_NEW
  };

 protected:
  /* Covariance matrix of the preintegrated measurements
   * COVARIANCE OF: [PreintROTATION PreintPOSITION PreintVELOCITY BiasAcc BiasOmega]
   * (first-order propagation from *measurementCovariance*).
   * PreintegratedCombinedMeasurements also include the biases and keep the correlation
   * between the preintegrated measurements and the biases
   */
  Eigen::Matrix<double, 15, 15> preintMeasCov_;


  friend class CombinedImuFactor;

 public:

  PreintegratedCombinedMeasurements() {}

  PreintegratedCombinedMeasurements(
      const boost::shared_ptr<Params>& p,
      const imuBias::ConstantBias& biasHat = imuBias::ConstantBias())
      : PreintegrationType(p, biasHat) {
    preintMeasCov_.setZero();
  }



  void resetIntegration() override;

  Params& p() const { return *boost::static_pointer_cast<Params>(this->p_);}

  Matrix preintMeasCov() const { return preintMeasCov_; }

  void print(const std::string& s = "Preintegrated Measurements:") const override;
  bool equals(const PreintegratedCombinedMeasurements& expected, double tol = 1e-9) const;


  void integrateMeasurement(const Vector3& measuredAcc,
      const Vector3& measuredOmega, const double dt) override;


#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V4
  PreintegratedCombinedMeasurements(const imuBias::ConstantBias& biasHat,
      const Matrix3& measuredAccCovariance,
      const Matrix3& measuredOmegaCovariance,
      const Matrix3& integrationErrorCovariance,
      const Matrix3& biasAccCovariance, const Matrix3& biasOmegaCovariance,
      const Matrix6& biasAccOmegaInt, const bool use2ndOrderIntegration = true);
#endif

 private:
  friend class boost::serialization::access;
  template <class ARCHIVE>
  void serialize(ARCHIVE& ar, const unsigned int /*version*/) {
    ar& BOOST_SERIALIZATION_BASE_OBJECT_NVP(PreintegrationType);
    ar& BOOST_SERIALIZATION_NVP(preintMeasCov_);
  }

public:
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};

class CombinedImuFactor: public NoiseModelFactor6<Pose3, Vector3, Pose3,
    Vector3, imuBias::ConstantBias, imuBias::ConstantBias> {
public:

private:

  typedef CombinedImuFactor This;
  typedef NoiseModelFactor6<Pose3, Vector3, Pose3, Vector3,
      imuBias::ConstantBias, imuBias::ConstantBias> Base;

  PreintegratedCombinedMeasurements _PIM_;

  CombinedImuFactor() {}

public:

#if !defined(_MSC_VER) && __GNUC__ == 4 && __GNUC_MINOR__ > 5
  typedef typename boost::shared_ptr<CombinedImuFactor> shared_ptr;
#else
  typedef boost::shared_ptr<CombinedImuFactor> shared_ptr;
#endif

  CombinedImuFactor(
      Key pose_i, Key vel_i, Key pose_j, Key vel_j, Key bias_i, Key bias_j,
      const PreintegratedCombinedMeasurements& preintegratedMeasurements);

  virtual ~CombinedImuFactor() {}

  virtual gtsam::NonlinearFactor::shared_ptr clone() const;

  virtual void print(const std::string& s, const KeyFormatter& keyFormatter =
      DefaultKeyFormatter) const;

  virtual bool equals(const NonlinearFactor& expected, double tol = 1e-9) const;

  const PreintegratedCombinedMeasurements& preintegratedMeasurements() const {
    return _PIM_;
  }

  Vector evaluateError(const Pose3& pose_i, const Vector3& vel_i,
      const Pose3& pose_j, const Vector3& vel_j,
      const imuBias::ConstantBias& bias_i, const imuBias::ConstantBias& bias_j,
      boost::optional<Matrix&> H1 = boost::none, boost::optional<Matrix&> H2 =
          boost::none, boost::optional<Matrix&> H3 = boost::none,
      boost::optional<Matrix&> H4 = boost::none, boost::optional<Matrix&> H5 =
          boost::none, boost::optional<Matrix&> H6 = boost::none) const;

#ifdef GTSAM_ALLOW_DEPRECATED_SINCE_V4
  typedef gtsam::PreintegratedCombinedMeasurements CombinedPreintegratedMeasurements;

  CombinedImuFactor(Key pose_i, Key vel_i, Key pose_j, Key vel_j, Key bias_i,
                    Key bias_j, const CombinedPreintegratedMeasurements& pim,
                    const Vector3& n_gravity, const Vector3& omegaCoriolis,
                    const boost::optional<Pose3>& body_P_sensor = boost::none,
                    const bool use2ndOrderCoriolis = false);

  // @deprecated use PreintegrationBase::predict
  static void Predict(const Pose3& pose_i, const Vector3& vel_i, Pose3& pose_j,
                      Vector3& vel_j, const imuBias::ConstantBias& bias_i,
                      CombinedPreintegratedMeasurements& pim,
                      const Vector3& n_gravity, const Vector3& omegaCoriolis,
                      const bool use2ndOrderCoriolis = false);
#endif

private:

  friend class boost::serialization::access;
  template<class ARCHIVE>
  void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
    ar & boost::serialization::make_nvp("NoiseModelFactor6",
         boost::serialization::base_object<Base>(*this));
    ar & BOOST_SERIALIZATION_NVP(_PIM_);
  }

public:
  EIGEN_MAKE_ALIGNED_OPERATOR_NEW
};
// class CombinedImuFactor

}