FlexibleKalmanBase.h File Reference

Header. More...

#include <osvr/Util/EigenCoreGeometry.h>
#include <type_traits>

Go to the source code of this file.

Classes
struct	osvr::kalman::types::HasDimensionBase
struct	osvr::kalman::HasDimension< DIM >
	Convenience base class for things (like states and measurements) that have a dimension. More...
struct	osvr::kalman::types::detail::Dimension_impl< T, typename >
struct	osvr::kalman::types::detail::Dimension_impl< DimensionConstant< n >, void >
struct	osvr::kalman::types::detail::Dimension_impl< T, typename std::enable_if< std::is_base_of< HasDimensionBase, T >::value >::type >

Namespaces
	osvr
	The main namespace for all C++ elements of the framework, internal and external.
	osvr::kalman
	Header-only framework for building Kalman-style filters, prediction, and sensor fusion.
	osvr::kalman::types
	Type aliases, including template type aliases.

Macros
#define	OSVR_KALMAN_DEBUG_OUTPUT(Name, Value)

Typedefs
using	osvr::kalman::types::Scalar = double
	Common scalar type.
using	osvr::kalman::types::DimensionType = std::size_t
	Type for dimensions.
template<DimensionType n>
using	osvr::kalman::types::DimensionConstant = std::integral_constant< DimensionType, n >
	Type constant for dimensions.
template<typename T >
using	osvr::kalman::types::Dimension = typename detail::Dimension_impl< T >::type
	Given a state or measurement, get the dimension as a std::integral_constant.
template<typename FilterType >
using	osvr::kalman::types::StateType = typename FilterType::State
	Given a filter type, get the state type.
template<typename FilterType >
using	osvr::kalman::types::ProcessModelType = typename FilterType::ProcessModel
	Given a filter type, get the process model type.
template<DimensionType n>
using	osvr::kalman::types::Vector = Eigen::Matrix< Scalar, n, 1 >
	A vector of length n.
template<typename T >
using	osvr::kalman::types::DimVector = Vector< Dimension< T >::value >
	A vector of length = dimension of T.
template<DimensionType n>
using	osvr::kalman::types::SquareMatrix = Eigen::Matrix< Scalar, n, n >
	A square matrix, n x n.
template<typename T >
using	osvr::kalman::types::DimSquareMatrix = SquareMatrix< Dimension< T >::value >
	A square matrix, n x n, where n is the dimension of T.
template<DimensionType n>
using	osvr::kalman::types::DiagonalMatrix = Eigen::DiagonalMatrix< Scalar, n >
	A square diagonal matrix, n x n.
template<typename T >
using	osvr::kalman::types::DimDiagonalMatrix = DiagonalMatrix< Dimension< T >::value >
	A square diagonal matrix, n x n, where n is the dimension of T.
template<DimensionType m, DimensionType n>
using	osvr::kalman::types::Matrix = Eigen::Matrix< Scalar, m, n >
	A matrix with rows = m, cols = n.
template<typename T , typename U >
using	osvr::kalman::types::DimMatrix = Matrix< Dimension< T >::value, Dimension< U >::value >
	A matrix with rows = dimension of T, cols = dimension of U.

Functions
template<typename StateType , typename ProcessModelType >
types::DimSquareMatrix< StateType >	osvr::kalman::predictErrorCovariance (StateType const &state, ProcessModelType &processModel, double dt)
	Computes P-. More...

Detailed Description

Header.

Date

2015

Author

Sensics, Inc. http://sensics.com/osvr