mrpt::slam::CICP::TConfigParams Class Reference

The ICP algorithm configuration data. More...

#include <mrpt/slam/CICP.h>

Inheritance diagram for mrpt::slam::CICP::TConfigParams:

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List of all members.

Public Member Functions
	TConfigParams ()
	Initializer for default values:.
void	loadFromConfigFile (const mrpt::utils::CConfigFileBase &source, const std::string &section)
	See utils::CLoadableOptions.
void	dumpToTextStream (CStream &out) const
	See utils::CLoadableOptions.
Public Attributes
TICPAlgorithm	ICP_algorithm
	The algorithm to use (default: icpClassic) See http://www.mrpt.org/Scan_Matching_Algorithms for details.
bool	onlyClosestCorrespondences
	The usual approach: to consider only the closest correspondence for each local point (Default to true).
bool	onlyUniqueRobust
	Apart of "onlyClosestCorrespondences=true", if this option is enabled only the closest correspondence for each reference point will be kept (default=false).
unsigned int	maxIterations
	Maximum number of iterations to run.
float	thresholdDist
	Initial threshold distance for two points to become a correspondence.
float	thresholdAng
float	ALFA
	The scale factor for threshold everytime convergence is achieved.
float	smallestThresholdDist
	The size for threshold such that iterations will stop, since it is considered precise enough.
float	covariance_varPoints
	This is the normalization constant $\sigma^2_p$ that is used to scale the whole 3x3 covariance.
bool	doRANSAC
	Perform a RANSAC step after the ICP convergence, to obtain a better estimation of the pose PDF.
unsigned int	ransac_minSetSize
	RANSAC-step options:.
unsigned int	ransac_maxSetSize
unsigned int	ransac_nSimulations
float	ransac_mahalanobisDistanceThreshold
	RANSAC-step options:.
float	normalizationStd
	RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG).
bool	ransac_fuseByCorrsMatch
	RANSAC-step options:.
float	ransac_fuseMaxDiffXY
	RANSAC-step options:.
float	ransac_fuseMaxDiffPhi
float	kernel_rho
	Cauchy kernel rho, for estimating the optimal transformation covariance, in meters (default = 0.07m).
bool	use_kernel
	Whether to use kernel_rho to smooth distances, or use distances directly (default=true).
float	Axy_aprox_derivatives
	The size of the perturbance in x & y used to estimate the Jacobians of the square error (in LM & IKF methods, default=0.05).
float	LM_initial_lambda
	The initial value of the lambda parameter in the LM method (default=1e-4).

Detailed Description

The ICP algorithm configuration data.

Definition at line 71 of file CICP.h.

Constructor & Destructor Documentation

mrpt::slam::CICP::TConfigParams::TConfigParams ( )

Initializer for default values:.

Member Function Documentation

void mrpt::slam::CICP::TConfigParams::dumpToTextStream ( CStream & out ) const [virtual]

See utils::CLoadableOptions.

Implements mrpt::utils::CLoadableOptions.

void mrpt::slam::CICP::TConfigParams::loadFromConfigFile	(	const mrpt::utils::CConfigFileBase &	source,
		const std::string &	section
	)			`[virtual]`

See utils::CLoadableOptions.

Implements mrpt::utils::CLoadableOptions.

Member Data Documentation

float mrpt::slam::CICP::TConfigParams::ALFA

The scale factor for threshold everytime convergence is achieved.

Definition at line 112 of file CICP.h.

float mrpt::slam::CICP::TConfigParams::Axy_aprox_derivatives

The size of the perturbance in x & y used to estimate the Jacobians of the square error (in LM & IKF methods, default=0.05).

Definition at line 163 of file CICP.h.

float mrpt::slam::CICP::TConfigParams::covariance_varPoints

This is the normalization constant $\sigma^2_p$ that is used to scale the whole 3x3 covariance.

This has a default value of $ (0.02)^2 $ , that is, a 2cm sigma. See the paper: ....

Definition at line 122 of file CICP.h.

bool mrpt::slam::CICP::TConfigParams::doRANSAC

Perform a RANSAC step after the ICP convergence, to obtain a better estimation of the pose PDF.

Definition at line 126 of file CICP.h.

TICPAlgorithm mrpt::slam::CICP::TConfigParams::ICP_algorithm

The algorithm to use (default: icpClassic) See http://www.mrpt.org/Scan_Matching_Algorithms for details.

Definition at line 92 of file CICP.h.

float mrpt::slam::CICP::TConfigParams::kernel_rho

Cauchy kernel rho, for estimating the optimal transformation covariance, in meters (default = 0.07m).

Definition at line 155 of file CICP.h.

float mrpt::slam::CICP::TConfigParams::LM_initial_lambda

The initial value of the lambda parameter in the LM method (default=1e-4).

Definition at line 167 of file CICP.h.

unsigned int mrpt::slam::CICP::TConfigParams::maxIterations

Maximum number of iterations to run.

Definition at line 104 of file CICP.h.

float mrpt::slam::CICP::TConfigParams::normalizationStd

RANSAC-step option: The standard deviation in X,Y of landmarks/points which are being matched (used to compute covariances in the SoG).

See also:: CICP::robustRigidTransformation

Definition at line 141 of file CICP.h.

bool mrpt::slam::CICP::TConfigParams::onlyClosestCorrespondences

The usual approach: to consider only the closest correspondence for each local point (Default to true).

Definition at line 96 of file CICP.h.

bool mrpt::slam::CICP::TConfigParams::onlyUniqueRobust

Apart of "onlyClosestCorrespondences=true", if this option is enabled only the closest correspondence for each reference point will be kept (default=false).

Definition at line 100 of file CICP.h.

bool mrpt::slam::CICP::TConfigParams::ransac_fuseByCorrsMatch

RANSAC-step options:.