#include <NoiseModel.h>

Inheritance diagram for gtsam::noiseModel::Robust:

Public Types
typedef std::shared_ptr< Robust >	shared_ptr

Public Types inherited from gtsam::noiseModel::Base
typedef std::shared_ptr< Base >	shared_ptr

Public Member Functions
bool	equals (const Base &expected, double tol=1e-9) const override

double	loss (const double squared_distance) const override
	Compute loss from the m-estimator using the Mahalanobis distance. More...

const NoiseModel::shared_ptr &	noise () const
	Return the contained noise model. More...

void	print (const std::string &name) const override

	Robust ()
	Default Constructor for serialization. More...

	Robust (const RobustModel::shared_ptr robust, const NoiseModel::shared_ptr noise)
	Constructor. More...

const RobustModel::shared_ptr &	robust () const
	Return the contained robust error function. More...

double	squaredMahalanobisDistance (const Vector &v) const override
	Squared Mahalanobis distance v'R'Rv = <Rv,R*v> More...

Vector	unweightedWhiten (const Vector &v) const override

Vector	unwhiten (const Vector &) const override
	Unwhiten an error vector. More...

double	weight (const Vector &v) const override

Vector	whiten (const Vector &v) const override
	Whiten an error vector. More...

Matrix	Whiten (const Matrix &A) const override
	Whiten a matrix. More...

virtual void	WhitenSystem (Vector &b) const

void	WhitenSystem (std::vector< Matrix > &A, Vector &b) const override

void	WhitenSystem (Matrix &A, Vector &b) const override

void	WhitenSystem (Matrix &A1, Matrix &A2, Vector &b) const override

void	WhitenSystem (Matrix &A1, Matrix &A2, Matrix &A3, Vector &b) const override

	~Robust () override
	Destructor. More...

Public Member Functions inherited from gtsam::noiseModel::Base
	Base (size_t dim=1)
	primary constructor More...

size_t	dim () const
	Dimensionality. More...

virtual bool	isConstrained () const
	true if a constrained noise model, saves slow/clumsy dynamic casting More...

virtual bool	isUnit () const
	true if a unit noise model, saves slow/clumsy dynamic casting More...

virtual double	mahalanobisDistance (const Vector &v) const
	Mahalanobis distance. More...

virtual Vector	sigmas () const
	Calculate standard deviations. More...

virtual void	unwhitenInPlace (Vector &v) const

virtual void	unwhitenInPlace (Eigen::Block< Vector > &v) const

virtual void	whitenInPlace (Vector &v) const

virtual void	whitenInPlace (Eigen::Block< Vector > &v) const

virtual	~Base ()

Static Public Member Functions
static shared_ptr	Create (const RobustModel::shared_ptr &robust, const NoiseModel::shared_ptr noise)

Protected Types
typedef noiseModel::Base	NoiseModel

typedef mEstimator::Base	RobustModel

Protected Attributes
const NoiseModel::shared_ptr	noise_
	noise model used More...

const RobustModel::shared_ptr	robust_
	robust error function used More...

Protected Attributes inherited from gtsam::noiseModel::Base
size_t	dim_

Detailed Description

Base class for robust error models The robust M-estimators above simply tell us how to re-weight the residual, and are isotropic kernels, in that they do not allow for correlated noise. They also have no way to scale the residual values, e.g., dividing by a single standard deviation. Hence, the actual robust noise model below does this scaling/whitening in sequence, by passing both a standard noise model and a robust estimator.

Taking as an example noise = Isotropic::Create(d, sigma), we first divide the residuals uw = |Ax-b| by sigma by "whitening" the system (A,b), obtaining r = |Ax-b|/sigma, and then we pass the now whitened residual 'r' through the robust M-estimator. This is currently done by multiplying with sqrt(w), because the residuals will be squared again in error, yielding 0.5 w(r)*r^2.

In other words, while sigma is expressed in the native residual units, a parameter like k in the Huber norm is expressed in whitened units, i.e., "nr of sigmas".

Definition at line 657 of file NoiseModel.h.

Member Typedef Documentation

◆ NoiseModel

typedef noiseModel::Base gtsam::noiseModel::Robust::NoiseModel

protected

Definition at line 663 of file NoiseModel.h.

◆ RobustModel

typedef mEstimator::Base gtsam::noiseModel::Robust::RobustModel

protected

Definition at line 662 of file NoiseModel.h.

◆ shared_ptr

typedef std::shared_ptr<Robust> gtsam::noiseModel::Robust::shared_ptr

Definition at line 659 of file NoiseModel.h.

Constructor & Destructor Documentation

◆ Robust() [1/2]

gtsam::noiseModel::Robust::Robust ( )

inline

Default Constructor for serialization.

Definition at line 671 of file NoiseModel.h.

◆ Robust() [2/2]

gtsam::noiseModel::Robust::Robust	(	const RobustModel::shared_ptr	robust,
		const NoiseModel::shared_ptr	noise
	)

inline

Constructor.

Definition at line 674 of file NoiseModel.h.

◆ ~Robust()

gtsam::noiseModel::Robust::~Robust ( )

inlineoverride

Destructor.

Definition at line 678 of file NoiseModel.h.

Member Function Documentation

◆ Create()

Robust::shared_ptr gtsam::noiseModel::Robust::Create	(	const RobustModel::shared_ptr &	robust,
		const NoiseModel::shared_ptr	noise
	)

static

Definition at line 704 of file NoiseModel.cpp.

◆ equals()

bool gtsam::noiseModel::Robust::equals	(	const Base &	expected,
		double	tol = `1e-9`
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 666 of file NoiseModel.cpp.

◆ loss()

double gtsam::noiseModel::Robust::loss ( const double squared_distance ) const

inlineoverridevirtual

Compute loss from the m-estimator using the Mahalanobis distance.

Reimplemented from gtsam::noiseModel::Base.

Definition at line 697 of file NoiseModel.h.

◆ noise()

const NoiseModel::shared_ptr& gtsam::noiseModel::Robust::noise ( ) const

inline

Return the contained noise model.

Definition at line 687 of file NoiseModel.h.

◆ print()

void gtsam::noiseModel::Robust::print ( const std::string & name ) const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 661 of file NoiseModel.cpp.

◆ robust()

const RobustModel::shared_ptr& gtsam::noiseModel::Robust::robust ( ) const

inline

Return the contained robust error function.

Definition at line 684 of file NoiseModel.h.

◆ squaredMahalanobisDistance()

double gtsam::noiseModel::Robust::squaredMahalanobisDistance ( const Vector & v ) const

inlineoverridevirtual

Squared Mahalanobis distance v'*R'*R*v = <R*v,R*v>

Reimplemented from gtsam::noiseModel::Base.

Definition at line 703 of file NoiseModel.h.

◆ unweightedWhiten()

Vector gtsam::noiseModel::Robust::unweightedWhiten ( const Vector & v ) const

overridevirtual

Useful function for robust noise models to get the unweighted but whitened error

Reimplemented from gtsam::noiseModel::Base.

Definition at line 697 of file NoiseModel.cpp.

◆ unwhiten()

Vector gtsam::noiseModel::Robust::unwhiten ( const Vector & v ) const

inlineoverridevirtual

Unwhiten an error vector.

Implements gtsam::noiseModel::Base.

Definition at line 694 of file NoiseModel.h.

◆ weight()

double gtsam::noiseModel::Robust::weight ( const Vector & v ) const

overridevirtual

get the weight from the effective loss function on residual vector v

Reimplemented from gtsam::noiseModel::Base.

Definition at line 700 of file NoiseModel.cpp.

◆ whiten()

Vector gtsam::noiseModel::Robust::whiten ( const Vector & v ) const

inlineoverridevirtual

Whiten an error vector.

Implements gtsam::noiseModel::Base.

Definition at line 690 of file NoiseModel.h.

◆ Whiten()

Matrix gtsam::noiseModel::Robust::Whiten ( const Matrix & H ) const

inlineoverridevirtual

Whiten a matrix.

Implements gtsam::noiseModel::Base.

Definition at line 692 of file NoiseModel.h.

◆ WhitenSystem() [1/5]

void gtsam::noiseModel::Robust::WhitenSystem ( Vector & b ) const

virtual

Definition at line 672 of file NoiseModel.cpp.

◆ WhitenSystem() [2/5]

void gtsam::noiseModel::Robust::WhitenSystem	(	std::vector< Matrix > &	A,
		Vector &	b
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 677 of file NoiseModel.cpp.

◆ WhitenSystem() [3/5]

void gtsam::noiseModel::Robust::WhitenSystem	(	Matrix &	A,
		Vector &	b
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 682 of file NoiseModel.cpp.

◆ WhitenSystem() [4/5]

void gtsam::noiseModel::Robust::WhitenSystem	(	Matrix &	A1,
		Matrix &	A2,
		Vector &	b
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 687 of file NoiseModel.cpp.

◆ WhitenSystem() [5/5]

void gtsam::noiseModel::Robust::WhitenSystem	(	Matrix &	A1,
		Matrix &	A2,
		Matrix &	A3,
		Vector &	b
	)		const

overridevirtual

Implements gtsam::noiseModel::Base.

Definition at line 692 of file NoiseModel.cpp.

Member Data Documentation

◆ noise_

const NoiseModel::shared_ptr gtsam::noiseModel::Robust::noise_

protected

noise model used

Definition at line 666 of file NoiseModel.h.

◆ robust_

const RobustModel::shared_ptr gtsam::noiseModel::Robust::robust_

protected

robust error function used

Definition at line 665 of file NoiseModel.h.

The documentation for this class was generated from the following files:

Public Types

Public Member Functions

Static Public Member Functions

Protected Types

Protected Attributes

Detailed Description

Member Typedef Documentation

◆ NoiseModel

◆ RobustModel

◆ shared_ptr

Constructor & Destructor Documentation

◆ Robust() [1/2]

◆ Robust() [2/2]

◆ ~Robust()

Member Function Documentation

◆ Create()

◆ equals()

◆ loss()

◆ noise()

◆ print()

◆ robust()

◆ squaredMahalanobisDistance()

◆ unweightedWhiten()

◆ unwhiten()

◆ weight()

◆ whiten()

◆ Whiten()

◆ WhitenSystem() [1/5]

◆ WhitenSystem() [2/5]

◆ WhitenSystem() [3/5]

◆ WhitenSystem() [4/5]

◆ WhitenSystem() [5/5]

Member Data Documentation

◆ noise_

◆ robust_