osvr::kalman Namespace Reference

Header-only framework for building Kalman-style filters, prediction, and sensor fusion. More...

Namespaces
	matrix_exponential_map
	types
	Type aliases, including template type aliases.

Classes
class	AbsoluteOrientationBase
singleton	AbsoluteOrientationMeasurement
class	AbsoluteOrientationMeasurement< pose_externalized_rotation::State >
	AbsoluteOrientationMeasurement with a pose_externalized_rotation::State. More...
class	AbsolutePositionBase
singleton	AbsolutePositionMeasurement
class	AbsolutePositionMeasurement< pose_externalized_rotation::State >
	AbsolutePositionMeasurement with a pose_externalized_rotation::State. More...
singleton	AngularVelocityMeasurement
class	AngularVelocityMeasurement< orient_externalized_rotation::State >
class	AngularVelocityMeasurement< pose_externalized_rotation::State >
	AngularVelocityMeasurement with a pose_externalized_rotation::State. More...
class	AugmentedProcessModel
class	AugmentedState
class	ConstantProcess
class	FlexibleKalmanFilter
struct	HasDimension
class	OrientationConstantVelocityProcessModel
	A model for a 3DOF pose (with angular velocity) More...
class	PoseConstantVelocityProcessModel
	A constant-velocity model for a 6DOF pose (with velocities) More...
class	PoseDampedConstantVelocityProcessModel
class	PoseSeparatelyDampedConstantVelocityProcessModel
class	PureVectorState

Typedefs
template<typename ModelA , typename ModelB >
using	DeducedAugmentedProcessModel = AugmentedProcessModel< typename std::remove_const< ModelA >::type, typename std::remove_const< ModelB >::type >
template<typename StateA , typename StateB >
using	DeducedAugmentedState = AugmentedState< typename std::remove_const< StateA >::type, typename std::remove_const< StateB >::type >

Functions
template<typename ModelA , typename ModelB >
DeducedAugmentedProcessModel < ModelA, ModelB >	makeAugmentedProcessModel (ModelA &a, ModelB &b)
template<typename StateA , typename StateB >
DeducedAugmentedState< StateA, StateB >	makeAugmentedState (StateA &a, StateB &b)
	Factory function, akin to std::tie(), to make an augmented state.
template<typename StateType , typename ProcessModelType >
types::DimSquareMatrix< StateType >	predictErrorCovariance (StateType const &state, ProcessModelType &processModel, double dt)
template<typename StateType , typename ProcessModelType , typename MeasurementType >
CorrectionInProgress < StateType, MeasurementType >	beginCorrection (StateType &state, ProcessModelType &processModel, MeasurementType &meas)
template<typename StateType , typename ProcessModelType , typename MeasurementType >
bool	correct (StateType &state, ProcessModelType &processModel, MeasurementType &meas, bool cancelIfNotFinite=true)
template<typename Derived >
Eigen::Matrix3d	makeSkewSymmetrixCrossProductMatrix (Eigen::MatrixBase< Derived > const &v)

Detailed Description

Header-only framework for building Kalman-style filters, prediction, and sensor fusion.

Typedef Documentation

template<typename ModelA , typename ModelB >

using osvr::kalman::DeducedAugmentedProcessModel = typedef AugmentedProcessModel<typename std::remove_const<ModelA>::type, typename std::remove_const<ModelB>::type>

Template alias to make removing const from the deduced types less verbose/painful.

Definition at line 88 of file AugmentedProcessModel.h.

template<typename StateA , typename StateB >

using osvr::kalman::DeducedAugmentedState = typedef AugmentedState<typename std::remove_const<StateA>::type, typename std::remove_const<StateB>::type>

Template alias to make removing const from the deduced types less verbose/painful.

Definition at line 130 of file AugmentedState.h.

Function Documentation

template<typename ModelA , typename ModelB >

DeducedAugmentedProcessModel<ModelA, ModelB> osvr::kalman::makeAugmentedProcessModel ( ModelA &  a, ModelB &  b  )

inline

Factory function, akin to std::tie(), to make an augmented process model.

Definition at line 94 of file AugmentedProcessModel.h.

template<typename StateType , typename ProcessModelType >

types::DimSquareMatrix<StateType> osvr::kalman::predictErrorCovariance ( StateType const &  state, ProcessModelType &  processModel, double  dt  )

inline

Computes P-

Usage is optional, most likely called from the process model updateState()` method.

Definition at line 135 of file FlexibleKalmanBase.h.

template<typename StateType , typename ProcessModelType , typename MeasurementType >

CorrectionInProgress<StateType, MeasurementType> osvr::kalman::beginCorrection ( StateType &  state, ProcessModelType &  processModel, MeasurementType &  meas  )

inline

Dimension of measurement

Dimension of state

Measurement Jacobian

Measurement covariance

State error covariance

The kalman gain stuff to not invert (called P12 in TAG)

the stuff to invert for the kalman gain also sometimes called S or the "Innovation Covariance"

More computation is done in initializers/constructor

Definition at line 135 of file FlexibleKalmanCorrect.h.

template<typename StateType , typename ProcessModelType , typename MeasurementType >

bool osvr::kalman::correct ( StateType &  state, ProcessModelType &  processModel, MeasurementType &  meas, bool  cancelIfNotFinite = true  )

inline

Parameters

cancelIfNotFinite

If the state correction or new error covariance is detected to contain non-finite values, should we cancel the correction and not apply it?

Returns

true if correction completed

Definition at line 58 of file FlexibleKalmanFilter.h.

template<typename Derived >

Eigen::Matrix3d osvr::kalman::makeSkewSymmetrixCrossProductMatrix ( Eigen::MatrixBase< Derived > const &  v )

inline

Produces the "hat matrix" that produces the same result as performing a cross-product with v. This is the same as the "capital omega" skew-symmetrix matrix used by a matrix-exponential-map rotation vector.

Parameters

v	a 3D vector

Returns

a matrix M such that for some 3D vector u, Mu = v x u.

Definition at line 48 of file MatrixExponentialMap.h.