336 lines
11 KiB
C++
336 lines
11 KiB
C++
/* ----------------------------------------------------------------------------
|
|
|
|
* 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 ImuFactor.h
|
|
* @author Luca Carlone
|
|
* @author Stephen Williams
|
|
* @author Richard Roberts
|
|
* @author Vadim Indelman
|
|
* @author David Jensen
|
|
* @author Frank Dellaert
|
|
**/
|
|
|
|
#pragma once
|
|
|
|
/* GTSAM includes */
|
|
#include <gtsam/nonlinear/NonlinearFactor.h>
|
|
#include <gtsam/navigation/ManifoldPreintegration.h>
|
|
#include <gtsam/navigation/TangentPreintegration.h>
|
|
#include <gtsam/base/debug.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.
|
|
*
|
|
* 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.
|
|
*
|
|
* 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.
|
|
* Available in this repo as "PreintegratedIMUJacobians.pdf".
|
|
* [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.
|
|
*/
|
|
|
|
/**
|
|
* PreintegratedImuMeasurements accumulates (integrates) the IMU measurements
|
|
* (rotation rates and accelerations) and the corresponding covariance matrix.
|
|
* The measurements are then used to build the Preintegrated IMU factor.
|
|
* Integration is done incrementally (ideally, one integrates the measurement
|
|
* as soon as it is received from the IMU) so as to avoid costly integration
|
|
* at time of factor construction.
|
|
*
|
|
* @ingroup navigation
|
|
*/
|
|
class GTSAM_EXPORT PreintegratedImuMeasurements: public PreintegrationType {
|
|
|
|
friend class ImuFactor;
|
|
friend class ImuFactor2;
|
|
|
|
protected:
|
|
|
|
Matrix9 preintMeasCov_; ///< COVARIANCE OF: [PreintROTATION PreintPOSITION PreintVELOCITY]
|
|
///< (first-order propagation from *measurementCovariance*).
|
|
|
|
public:
|
|
|
|
/// Default constructor for serialization and wrappers
|
|
PreintegratedImuMeasurements() {
|
|
preintMeasCov_.setZero();
|
|
}
|
|
|
|
/**
|
|
* Constructor, initializes the class with no measurements
|
|
* @param p Parameters, typically fixed in a single application
|
|
* @param biasHat Current estimate of acceleration and rotation rate biases
|
|
*/
|
|
PreintegratedImuMeasurements(const boost::shared_ptr<PreintegrationParams>& p,
|
|
const imuBias::ConstantBias& biasHat = imuBias::ConstantBias()) :
|
|
PreintegrationType(p, biasHat) {
|
|
preintMeasCov_.setZero();
|
|
}
|
|
|
|
/**
|
|
* Construct preintegrated directly from members: base class and preintMeasCov
|
|
* @param base PreintegrationType instance
|
|
* @param preintMeasCov Covariance matrix used in noise model.
|
|
*/
|
|
PreintegratedImuMeasurements(const PreintegrationType& base, const Matrix9& preintMeasCov)
|
|
: PreintegrationType(base),
|
|
preintMeasCov_(preintMeasCov) {
|
|
}
|
|
|
|
/// Virtual destructor
|
|
~PreintegratedImuMeasurements() override {
|
|
}
|
|
|
|
/// print
|
|
void print(const std::string& s = "Preintegrated Measurements:") const override;
|
|
|
|
/// equals
|
|
bool equals(const PreintegratedImuMeasurements& expected, double tol = 1e-9) const;
|
|
|
|
/// Re-initialize PreintegratedIMUMeasurements
|
|
void resetIntegration() override;
|
|
|
|
/**
|
|
* Add a single IMU measurement to the preintegration.
|
|
* Both accelerometer and gyroscope measurements are taken to be in the sensor
|
|
* frame and conversion to the body frame is handled by `body_P_sensor` in
|
|
* `PreintegrationParams`.
|
|
*
|
|
* @param measuredAcc Measured acceleration (as given by the sensor)
|
|
* @param measuredOmega Measured angular velocity (as given by the sensor)
|
|
* @param dt Time interval between this and the last IMU measurement
|
|
*/
|
|
void integrateMeasurement(const Vector3& measuredAcc,
|
|
const Vector3& measuredOmega, const double dt) override;
|
|
|
|
/// Add multiple measurements, in matrix columns
|
|
void integrateMeasurements(const Matrix& measuredAccs, const Matrix& measuredOmegas,
|
|
const Matrix& dts);
|
|
|
|
/// Return pre-integrated measurement covariance
|
|
Matrix preintMeasCov() const { return preintMeasCov_; }
|
|
|
|
#ifdef GTSAM_TANGENT_PREINTEGRATION
|
|
/// Merge in a different set of measurements and update bias derivatives accordingly
|
|
void mergeWith(const PreintegratedImuMeasurements& pim, Matrix9* H1, Matrix9* H2);
|
|
#endif
|
|
|
|
private:
|
|
/// Serialization function
|
|
friend class boost::serialization::access;
|
|
template<class ARCHIVE>
|
|
void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
|
|
namespace bs = ::boost::serialization;
|
|
ar & BOOST_SERIALIZATION_BASE_OBJECT_NVP(PreintegrationType);
|
|
ar & BOOST_SERIALIZATION_NVP(preintMeasCov_);
|
|
}
|
|
};
|
|
|
|
/**
|
|
* ImuFactor is a 5-ways factor involving previous state (pose and velocity of
|
|
* the vehicle at previous time step), current state (pose and velocity at
|
|
* current time step), and the bias estimate. Following the preintegration
|
|
* scheme proposed in [2], the ImuFactor includes many IMU measurements, which
|
|
* are "summarized" using the PreintegratedIMUMeasurements class.
|
|
* Note that this factor does not model "temporal consistency" of the biases
|
|
* (which are usually slowly varying quantities), which is up to the caller.
|
|
* See also CombinedImuFactor for a class that does this for you.
|
|
*
|
|
* @ingroup navigation
|
|
*/
|
|
class GTSAM_EXPORT ImuFactor: public NoiseModelFactorN<Pose3, Vector3, Pose3, Vector3,
|
|
imuBias::ConstantBias> {
|
|
private:
|
|
|
|
typedef ImuFactor This;
|
|
typedef NoiseModelFactorN<Pose3, Vector3, Pose3, Vector3,
|
|
imuBias::ConstantBias> Base;
|
|
|
|
PreintegratedImuMeasurements _PIM_;
|
|
|
|
public:
|
|
using Base::evaluateError;
|
|
|
|
/** Shorthand for a smart pointer to a factor */
|
|
#if !defined(_MSC_VER) && __GNUC__ == 4 && __GNUC_MINOR__ > 5
|
|
typedef typename boost::shared_ptr<ImuFactor> shared_ptr;
|
|
#else
|
|
typedef boost::shared_ptr<ImuFactor> shared_ptr;
|
|
#endif
|
|
|
|
/** Default constructor - only use for serialization */
|
|
ImuFactor() {}
|
|
|
|
/**
|
|
* Constructor
|
|
* @param pose_i Previous pose key
|
|
* @param vel_i Previous velocity key
|
|
* @param pose_j Current pose key
|
|
* @param vel_j Current velocity key
|
|
* @param bias Previous bias key
|
|
* @param preintegratedMeasurements The preintegreated measurements since the
|
|
* last pose.
|
|
*/
|
|
ImuFactor(Key pose_i, Key vel_i, Key pose_j, Key vel_j, Key bias,
|
|
const PreintegratedImuMeasurements& preintegratedMeasurements);
|
|
|
|
~ImuFactor() override {
|
|
}
|
|
|
|
/// @return a deep copy of this factor
|
|
gtsam::NonlinearFactor::shared_ptr clone() const override;
|
|
|
|
/// @name Testable
|
|
/// @{
|
|
GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, const ImuFactor&);
|
|
void print(const std::string& s = "", const KeyFormatter& keyFormatter =
|
|
DefaultKeyFormatter) const override;
|
|
bool equals(const NonlinearFactor& expected, double tol = 1e-9) const override;
|
|
/// @}
|
|
|
|
/** Access the preintegrated measurements. */
|
|
|
|
const PreintegratedImuMeasurements& preintegratedMeasurements() const {
|
|
return _PIM_;
|
|
}
|
|
|
|
/** implement functions needed to derive from Factor */
|
|
|
|
/// vector of errors
|
|
Vector evaluateError(const Pose3& pose_i, const Vector3& vel_i,
|
|
const Pose3& pose_j, const Vector3& vel_j,
|
|
const imuBias::ConstantBias& bias_i, OptionalMatrixType H1, OptionalMatrixType H2,
|
|
OptionalMatrixType H3, OptionalMatrixType H4, OptionalMatrixType H5) const override;
|
|
|
|
#ifdef GTSAM_TANGENT_PREINTEGRATION
|
|
/// Merge two pre-integrated measurement classes
|
|
static PreintegratedImuMeasurements Merge(
|
|
const PreintegratedImuMeasurements& pim01,
|
|
const PreintegratedImuMeasurements& pim12);
|
|
|
|
/// Merge two factors
|
|
static shared_ptr Merge(const shared_ptr& f01, const shared_ptr& f12);
|
|
#endif
|
|
|
|
private:
|
|
/** Serialization function */
|
|
friend class boost::serialization::access;
|
|
template<class ARCHIVE>
|
|
void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
|
|
// NoiseModelFactor5 instead of NoiseModelFactorN for backward compatibility
|
|
ar & boost::serialization::make_nvp("NoiseModelFactor5",
|
|
boost::serialization::base_object<Base>(*this));
|
|
ar & BOOST_SERIALIZATION_NVP(_PIM_);
|
|
}
|
|
};
|
|
// class ImuFactor
|
|
|
|
/**
|
|
* ImuFactor2 is a ternary factor that uses NavStates rather than Pose/Velocity.
|
|
* @ingroup navigation
|
|
*/
|
|
class GTSAM_EXPORT ImuFactor2 : public NoiseModelFactorN<NavState, NavState, imuBias::ConstantBias> {
|
|
private:
|
|
|
|
typedef ImuFactor2 This;
|
|
typedef NoiseModelFactorN<NavState, NavState, imuBias::ConstantBias> Base;
|
|
|
|
PreintegratedImuMeasurements _PIM_;
|
|
|
|
public:
|
|
|
|
/** Default constructor - only use for serialization */
|
|
ImuFactor2() {}
|
|
|
|
/**
|
|
* Constructor
|
|
* @param state_i Previous state key
|
|
* @param state_j Current state key
|
|
* @param bias Previous bias key
|
|
*/
|
|
ImuFactor2(Key state_i, Key state_j, Key bias,
|
|
const PreintegratedImuMeasurements& preintegratedMeasurements);
|
|
|
|
~ImuFactor2() override {
|
|
}
|
|
|
|
/// @return a deep copy of this factor
|
|
gtsam::NonlinearFactor::shared_ptr clone() const override;
|
|
|
|
/// @name Testable
|
|
/// @{
|
|
GTSAM_EXPORT friend std::ostream& operator<<(std::ostream& os, const ImuFactor2&);
|
|
void print(const std::string& s = "", const KeyFormatter& keyFormatter =
|
|
DefaultKeyFormatter) const override;
|
|
bool equals(const NonlinearFactor& expected, double tol = 1e-9) const override;
|
|
/// @}
|
|
|
|
/** Access the preintegrated measurements. */
|
|
|
|
const PreintegratedImuMeasurements& preintegratedMeasurements() const {
|
|
return _PIM_;
|
|
}
|
|
|
|
/** implement functions needed to derive from Factor */
|
|
|
|
/// vector of errors
|
|
Vector evaluateError(const NavState& state_i, const NavState& state_j,
|
|
const imuBias::ConstantBias& bias_i, //
|
|
OptionalMatrixType H1, OptionalMatrixType H2,
|
|
OptionalMatrixType H3) const override;
|
|
|
|
private:
|
|
|
|
/** Serialization function */
|
|
friend class boost::serialization::access;
|
|
template<class ARCHIVE>
|
|
void serialize(ARCHIVE & ar, const unsigned int /*version*/) {
|
|
// NoiseModelFactor3 instead of NoiseModelFactorN for backward compatibility
|
|
ar & boost::serialization::make_nvp("NoiseModelFactor3",
|
|
boost::serialization::base_object<Base>(*this));
|
|
ar & BOOST_SERIALIZATION_NVP(_PIM_);
|
|
}
|
|
};
|
|
// class ImuFactor2
|
|
|
|
template <>
|
|
struct traits<PreintegratedImuMeasurements> : public Testable<PreintegratedImuMeasurements> {};
|
|
|
|
template <>
|
|
struct traits<ImuFactor> : public Testable<ImuFactor> {};
|
|
|
|
template <>
|
|
struct traits<ImuFactor2> : public Testable<ImuFactor2> {};
|
|
|
|
} /// namespace gtsam
|