rgbdtools::MotionEstimationICPProbModel Class Reference

Motion estimation based on aligning sparse features against a persistent, dynamic model. More...

#include <motion_estimation_icp_prob_model.h>

Inheritance diagram for rgbdtools::MotionEstimationICPProbModel:

List of all members.

Public Member Functions
Matrix3fVector *	getCovariances ()
Matrix3fVector *	getCovariances ()
Vector3fVector *	getMeans ()
Vector3fVector *	getMeans ()
PointCloudFeature::Ptr	getModel ()
PointCloudFeature::Ptr	getModel ()
int	getModelSize () const
	Returns the number of points in the model built from the feature buffer.
int	getModelSize () const
	Returns the number of points in the model built from the feature buffer.
bool	getMotionEstimationImpl (RGBDFrame &frame, const AffineTransform &prediction, AffineTransform &motion)
	Main method for estimating the motion given an RGBD frame.
bool	getMotionEstimationImpl (RGBDFrame &frame, const AffineTransform &prediction, AffineTransform &motion)
	Main method for estimating the motion given an RGBD frame.
EIGEN_MAKE_ALIGNED_OPERATOR_NEW	MotionEstimationICPProbModel ()
	Constructor from ROS noehandles.
EIGEN_MAKE_ALIGNED_OPERATOR_NEW	MotionEstimationICPProbModel ()
	Constructor from ROS noehandles.
void	resetModel ()
void	resetModel ()
void	setMaxAssociationDistMahalanobis (double max_assoc_dist_mah)
void	setMaxAssociationDistMahalanobis (double max_assoc_dist_mah)
void	setMaxCorrespondenceDistEuclidean (double max_corresp_dist_eucl)
void	setMaxCorrespondenceDistEuclidean (double max_corresp_dist_eucl)
void	setMaxIterations (int max_iterations)
void	setMaxIterations (int max_iterations)
void	setMaxModelSize (int max_model_size)
void	setMaxModelSize (int max_model_size)
void	setMinCorrespondences (int min_correspondences)
void	setMinCorrespondences (int min_correspondences)
void	setNNearestNeighbors (int n_nearest_neighbors)
void	setNNearestNeighbors (int n_nearest_neighbors)
void	setTfEpsilonAngular (double tf_epsilon_angular)
void	setTfEpsilonAngular (double tf_epsilon_angular)
void	setTfEpsilonLinear (double tf_epsilon_linear)
void	setTfEpsilonLinear (double tf_epsilon_linear)
virtual	~MotionEstimationICPProbModel ()
	Default destructor.
virtual	~MotionEstimationICPProbModel ()
	Default destructor.
Private Member Functions
void	addToModel (const Vector3f &data_mean, const Matrix3f &data_cov)
	Adds a new point to the model.
void	addToModel (const Vector3f &data_mean, const Matrix3f &data_cov)
	Adds a new point to the model.
bool	alignICPEuclidean (const Vector3fVector &data_means, AffineTransform &correction)
	Performs ICP alignment using the Euclidean distance for corresopndences.
bool	alignICPEuclidean (const Vector3fVector &data_means, AffineTransform &correction)
	Performs ICP alignment using the Euclidean distance for corresopndences.
void	getCorrespEuclidean (const PointCloudFeature &data_cloud, IntVector &data_indices, IntVector &model_indices)
	Performs ICP alignment using the Euclidean distance for corresopndences.
void	getCorrespEuclidean (const PointCloudFeature &data_cloud, IntVector &data_indices, IntVector &model_indices)
	Performs ICP alignment using the Euclidean distance for corresopndences.
bool	getNNEuclidean (const PointFeature &data_point, int &eucl_nn_idx, double &eucl_dist_sq)
	Finds the nearest Euclidean neighbor.
bool	getNNEuclidean (const PointFeature &data_point, int &eucl_nn_idx, double &eucl_dist_sq)
	Finds the nearest Euclidean neighbor.
bool	getNNMahalanobis (const Vector3f &data_mean, const Matrix3f &data_cov, int &mah_nn_idx, double &mah_dist_sq, IntVector &indices, FloatVector &dists_sq)
	Finds the nearest Mahalanobis neighbor.
bool	getNNMahalanobis (const Vector3f &data_mean, const Matrix3f &data_cov, int &mah_nn_idx, double &mah_dist_sq, IntVector &indices, FloatVector &dists_sq)
	Finds the nearest Mahalanobis neighbor.
void	initializeModelFromData (const Vector3fVector &data_means, const Matrix3fVector &data_covariances)
	Initializes the (empty) model from a set of data means and covariances.
void	initializeModelFromData (const Vector3fVector &data_means, const Matrix3fVector &data_covariances)
	Initializes the (empty) model from a set of data means and covariances.
bool	saveModel (const std::string &filename)
bool	saveModel (const std::string &filename)
void	updateModelFromData (const Vector3fVector &data_means, const Matrix3fVector &data_covariances)
	Updates the (non-empty) model from a set of data means and covariances.
void	updateModelFromData (const Vector3fVector &data_means, const Matrix3fVector &data_covariances)
	Updates the (non-empty) model from a set of data means and covariances.
Private Attributes
Matrix3fVector	covariances_
	Vector of model feature covariances.
AffineTransform	f2b_
	Transform from fixed to moving frame.
Matrix3f	I_
	3x3 Identity matrix
double	max_assoc_dist_mah_
	Maximum Mahalanobis distance for associating points between the data and the model.
double	max_assoc_dist_mah_sq_
	Maximum squared Mahalanobis distance for associating points between the data and the model, derived.
double	max_corresp_dist_eucl_
	Maximum Euclidean correspondce distance for ICP.
double	max_corresp_dist_eucl_sq_
	Maximum Euclidean correspondce distance for ICP, derived.
int	max_iterations_
	Maximum number of ICP iterations.
int	max_model_size_
	Upper bound for how many features to store in the model.
Vector3fVector	means_
	Vector of model feature mean.
int	min_correspondences_
	Minimum number of correspondences for ICP to contuinue.
int	model_idx_
	Current intex in the ring buffer.
PointCloudFeature::Ptr	model_ptr_
	The model point cloud.
int	model_size_
	Current model size.
KdTree	model_tree_
	Kdtree of model_ptr_.
int	n_nearest_neighbors_
	How many euclidean neighbors to go through, in a brute force search of the closest Mahalanobis neighbor.
double	tf_epsilon_angular_
	Angular convergence criteria for ICP.
double	tf_epsilon_linear_
	Linear convergence criteria for ICP.

---

Detailed Description

Motion estimation based on aligning sparse features against a persistent, dynamic model.

The model is build from incoming features through a Kalman Filter update step.

Definition at line 42 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

---

Constructor & Destructor Documentation

rgbdtools::MotionEstimationICPProbModel::MotionEstimationICPProbModel

(

)

Constructor from ROS noehandles.

Parameters:

nh	the public nodehandle
nh_private	the private notehandle

Definition at line 28 of file motion_estimation_icp_prob_model.cpp.

rgbdtools::MotionEstimationICPProbModel::~MotionEstimationICPProbModel

(

)

[virtual]

Default destructor.

Definition at line 54 of file motion_estimation_icp_prob_model.cpp.

EIGEN_MAKE_ALIGNED_OPERATOR_NEW rgbdtools::MotionEstimationICPProbModel::MotionEstimationICPProbModel

(

)

Constructor from ROS noehandles.

Parameters:

nh	the public nodehandle
nh_private	the private notehandle

virtual rgbdtools::MotionEstimationICPProbModel::~MotionEstimationICPProbModel

(

)

[virtual]

Default destructor.

---

Member Function Documentation

void rgbdtools::MotionEstimationICPProbModel::addToModel	(	const Vector3f &	data_mean,
		const Matrix3f &	data_cov
	)		[private]

Adds a new point to the model.

The model is implemented using a rign buffer. If the number of points in the model has reached the maximum, the new point will overwrite the oldest model point

Parameters:

data_mean	3x1 data point means
data_cov	3x3 data point covariances

Definition at line 59 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::addToModel	(	const Vector3f &	data_mean,
		const Matrix3f &	data_cov
	)		[private]

Adds a new point to the model.

The model is implemented using a rign buffer. If the number of points in the model has reached the maximum, the new point will overwrite the oldest model point

Parameters:

data_mean	3x1 data point means
data_cov	3x3 data point covariances

bool rgbdtools::MotionEstimationICPProbModel::alignICPEuclidean	(	const Vector3fVector &	data_means,
		AffineTransform &	correction
	)		[private]

Performs ICP alignment using the Euclidean distance for corresopndences.

Parameters:

data_means	a vector of 3x1 matrices, repesenting the 3D positions of the features
correction	reference to the resulting transformation

Return values:

true	the motion estimation was successful
false	the motion estimation failed

bool rgbdtools::MotionEstimationICPProbModel::alignICPEuclidean	(	const Vector3fVector &	data_means,
		AffineTransform &	correction
	)		[private]

Performs ICP alignment using the Euclidean distance for corresopndences.

Parameters:

data_means	a vector of 3x1 matrices, repesenting the 3D positions of the features
correction	reference to the resulting transformation

Return values:

true	the motion estimation was successful
false	the motion estimation failed

Definition at line 159 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::getCorrespEuclidean	(	const PointCloudFeature &	data_cloud,
		IntVector &	data_indices,
		IntVector &	model_indices
	)		[private]

Performs ICP alignment using the Euclidean distance for corresopndences.

Parameters:

data_cloud	a pointcloud of the 3D positions of the features
data_indices	reference to a vector containting the resulting data indices
model_indices	reference to a vector containting the resulting model indices

void rgbdtools::MotionEstimationICPProbModel::getCorrespEuclidean	(	const PointCloudFeature &	data_cloud,
		IntVector &	data_indices,
		IntVector &	model_indices
	)		[private]

Performs ICP alignment using the Euclidean distance for corresopndences.

Parameters:

data_cloud	a pointcloud of the 3D positions of the features
data_indices	reference to a vector containting the resulting data indices
model_indices	reference to a vector containting the resulting model indices

Definition at line 219 of file motion_estimation_icp_prob_model.cpp.

Matrix3fVector* rgbdtools::MotionEstimationICPProbModel::getCovariances

(

)

[inline]

Definition at line 77 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

Matrix3fVector* rgbdtools::MotionEstimationICPProbModel::getCovariances

(

)

[inline]

Definition at line 77 of file rgbdtools_git/include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

Vector3fVector* rgbdtools::MotionEstimationICPProbModel::getMeans

(

)

[inline]

Definition at line 76 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

Vector3fVector* rgbdtools::MotionEstimationICPProbModel::getMeans

(

)

[inline]

Definition at line 76 of file rgbdtools_git/include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

PointCloudFeature::Ptr rgbdtools::MotionEstimationICPProbModel::getModel

(

)

[inline]

Definition at line 75 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

PointCloudFeature::Ptr rgbdtools::MotionEstimationICPProbModel::getModel

(

)

[inline]

Definition at line 75 of file rgbdtools_git/include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::getModelSize

(

)

const [inline, virtual]

Returns the number of points in the model built from the feature buffer.

Returns:

number of points in model

Reimplemented from rgbdtools::MotionEstimation.

Definition at line 73 of file rgbdtools_git/include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::getModelSize

(

)

const [inline, virtual]

Returns the number of points in the model built from the feature buffer.

Returns:

number of points in model

Reimplemented from rgbdtools::MotionEstimation.

Definition at line 73 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

bool rgbdtools::MotionEstimationICPProbModel::getMotionEstimationImpl	(	RGBDFrame &	frame,
		const AffineTransform &	prediction,
		AffineTransform &	motion
	)		[virtual]

Main method for estimating the motion given an RGBD frame.

Parameters:

frame	the current RGBD frame
prediction	the predicted motion (currently ignored)
motion	the (output) incremental motion, wrt the fixed frame

Return values:

true	the motion estimation was successful
false	the motion estimation failed

Todo:

: currently ignores prediction

Implements rgbdtools::MotionEstimation.

Definition at line 95 of file motion_estimation_icp_prob_model.cpp.

bool rgbdtools::MotionEstimationICPProbModel::getMotionEstimationImpl	(	RGBDFrame &	frame,
		const AffineTransform &	prediction,
		AffineTransform &	motion
	)		[virtual]

Main method for estimating the motion given an RGBD frame.

Parameters:

frame	the current RGBD frame
prediction	the predicted motion (currently ignored)
motion	the (output) incremental motion, wrt the fixed frame

Return values:

true	the motion estimation was successful
false	the motion estimation failed

Implements rgbdtools::MotionEstimation.

bool rgbdtools::MotionEstimationICPProbModel::getNNEuclidean	(	const PointFeature &	data_point,
		int &	eucl_nn_idx,
		double &	eucl_dist_sq
	)		[private]

Finds the nearest Euclidean neighbor.

Parameters:

data_point	the query 3D data point
eucl_nn_idx	reference to the resulting nearest neigbor index in the model
eucl_dist_sq	reference to the resulting squared distance

Return values:

true	a neighbor was found
false	a neighbor was not found

Definition at line 241 of file motion_estimation_icp_prob_model.cpp.

bool rgbdtools::MotionEstimationICPProbModel::getNNEuclidean	(	const PointFeature &	data_point,
		int &	eucl_nn_idx,
		double &	eucl_dist_sq
	)		[private]

Finds the nearest Euclidean neighbor.

Parameters:

data_point	the query 3D data point
eucl_nn_idx	reference to the resulting nearest neigbor index in the model
eucl_dist_sq	reference to the resulting squared distance

Return values:

true	a neighbor was found
false	a neighbor was not found

bool rgbdtools::MotionEstimationICPProbModel::getNNMahalanobis	(	const Vector3f &	data_mean,
		const Matrix3f &	data_cov,
		int &	mah_nn_idx,
		double &	mah_dist_sq,
		IntVector &	indices,
		FloatVector &	dists_sq
	)		[private]

Finds the nearest Mahalanobis neighbor.

Requests the K nearest Euclidean neighbors (K = n_nearest_neighbors_) using a kdtree, and performs a brute force search for the closest Mahalanobis nighbor. Reasonable values for K are 4 or 8.

Parameters:

data_mean	3x1 matrix of the query 3D data point mean
data_cov	3x3 matrix of the query 3D data point covariance
mah_nn_idx	reference to the resulting nearest neigbor index in the model
mah_dist_sq	reference to the resulting squared Mahalanobis distance
indices	cache vector, pre-allocated with n_nearest_neighbors_ size
dists_sq	cache vector, pre-allocated with n_nearest_neighbors_ size

Return values:

true	a neighbor was found
false	a neighbor was not found

Definition at line 263 of file motion_estimation_icp_prob_model.cpp.

bool rgbdtools::MotionEstimationICPProbModel::getNNMahalanobis	(	const Vector3f &	data_mean,
		const Matrix3f &	data_cov,
		int &	mah_nn_idx,
		double &	mah_dist_sq,
		IntVector &	indices,
		FloatVector &	dists_sq
	)		[private]

Finds the nearest Mahalanobis neighbor.

Requests the K nearest Euclidean neighbors (K = n_nearest_neighbors_) using a kdtree, and performs a brute force search for the closest Mahalanobis nighbor. Reasonable values for K are 4 or 8.

Parameters:

data_mean	3x1 matrix of the query 3D data point mean
data_cov	3x3 matrix of the query 3D data point covariance
mah_nn_idx	reference to the resulting nearest neigbor index in the model
mah_dist_sq	reference to the resulting squared Mahalanobis distance
indices	cache vector, pre-allocated with n_nearest_neighbors_ size
dists_sq	cache vector, pre-allocated with n_nearest_neighbors_ size

Return values:

true	a neighbor was found
false	a neighbor was not found

void rgbdtools::MotionEstimationICPProbModel::initializeModelFromData	(	const Vector3fVector &	data_means,
		const Matrix3fVector &	data_covariances
	)		[private]

Initializes the (empty) model from a set of data means and covariances.

Parameters:

data_means	vector of 3x1 data point means
data_covariances	vector of 3x3 data point covariances

Definition at line 312 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::initializeModelFromData	(	const Vector3fVector &	data_means,
		const Matrix3fVector &	data_covariances
	)		[private]

Initializes the (empty) model from a set of data means and covariances.

Parameters:

data_means	vector of 3x1 data point means
data_covariances	vector of 3x3 data point covariances

void rgbdtools::MotionEstimationICPProbModel::resetModel

(

)

void rgbdtools::MotionEstimationICPProbModel::resetModel

(

)

Definition at line 90 of file motion_estimation_icp_prob_model.cpp.

bool rgbdtools::MotionEstimationICPProbModel::saveModel

(

const std::string &

filename

)

[private]

bool rgbdtools::MotionEstimationICPProbModel::saveModel

(

const std::string &

filename

)

[private]

Todo:

also save Eigen means and covariances

Definition at line 382 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setMaxAssociationDistMahalanobis

(

double

max_assoc_dist_mah

)

void rgbdtools::MotionEstimationICPProbModel::setMaxAssociationDistMahalanobis

(

double

max_assoc_dist_mah

)

Definition at line 434 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setMaxCorrespondenceDistEuclidean

(

double

max_corresp_dist_eucl

)

void rgbdtools::MotionEstimationICPProbModel::setMaxCorrespondenceDistEuclidean

(

double

max_corresp_dist_eucl

)

Definition at line 441 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setMaxIterations

(

int

max_iterations

)

Definition at line 404 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setMaxIterations

(

int

max_iterations

)

void rgbdtools::MotionEstimationICPProbModel::setMaxModelSize

(

int

max_model_size

)

Definition at line 419 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setMaxModelSize

(

int

max_model_size

)

void rgbdtools::MotionEstimationICPProbModel::setMinCorrespondences

(

int

min_correspondences

)

void rgbdtools::MotionEstimationICPProbModel::setMinCorrespondences

(

int

min_correspondences

)

Definition at line 409 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setNNearestNeighbors

(

int

n_nearest_neighbors

)

Definition at line 414 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setNNearestNeighbors

(

int

n_nearest_neighbors

)

void rgbdtools::MotionEstimationICPProbModel::setTfEpsilonAngular

(

double

tf_epsilon_angular

)

Definition at line 429 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::setTfEpsilonAngular

(

double

tf_epsilon_angular

)

void rgbdtools::MotionEstimationICPProbModel::setTfEpsilonLinear

(

double

tf_epsilon_linear

)

void rgbdtools::MotionEstimationICPProbModel::setTfEpsilonLinear

(

double

tf_epsilon_linear

)

Definition at line 424 of file motion_estimation_icp_prob_model.cpp.

void rgbdtools::MotionEstimationICPProbModel::updateModelFromData	(	const Vector3fVector &	data_means,
		const Matrix3fVector &	data_covariances
	)		[private]

Updates the (non-empty) model from a set of data means and covariances.

Any data points which have a Mahalanobis neighbor in the model under a certain threshold distance get updated using a Kalman filter.

Any data points without a Mahalanobis neighbor get insterted as new model points.

Parameters:

data_means	vector of 3x1 data point means
data_covariances	vector of 3x3 data point covariances

void rgbdtools::MotionEstimationICPProbModel::updateModelFromData	(	const Vector3fVector &	data_means,
		const Matrix3fVector &	data_covariances
	)		[private]

Updates the (non-empty) model from a set of data means and covariances.

Any data points which have a Mahalanobis neighbor in the model under a certain threshold distance get updated using a Kalman filter.

Any data points without a Mahalanobis neighbor get insterted as new model points.

Parameters:

data_means	vector of 3x1 data point means
data_covariances	vector of 3x3 data point covariances

Definition at line 324 of file motion_estimation_icp_prob_model.cpp.

---

Member Data Documentation

Matrix3fVector rgbdtools::MotionEstimationICPProbModel::covariances_ [private]

Vector of model feature covariances.

Definition at line 134 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

AffineTransform rgbdtools::MotionEstimationICPProbModel::f2b_ [private]

Transform from fixed to moving frame.

Definition at line 140 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

Matrix3f rgbdtools::MotionEstimationICPProbModel::I_ [private]

3x3 Identity matrix

Definition at line 138 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::max_assoc_dist_mah_ [private]

Maximum Mahalanobis distance for associating points between the data and the model.

Definition at line 112 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::max_assoc_dist_mah_sq_ [private]

Maximum squared Mahalanobis distance for associating points between the data and the model, derived.

Definition at line 122 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::max_corresp_dist_eucl_ [private]

Maximum Euclidean correspondce distance for ICP.

Definition at line 116 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::max_corresp_dist_eucl_sq_ [private]

Maximum Euclidean correspondce distance for ICP, derived.

Definition at line 126 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::max_iterations_ [private]

Maximum number of ICP iterations.

Definition at line 92 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::max_model_size_ [private]

Upper bound for how many features to store in the model.

New features added beyond thi spoint will overwrite old features

Definition at line 104 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

Vector3fVector rgbdtools::MotionEstimationICPProbModel::means_ [private]

Vector of model feature mean.

Definition at line 133 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::min_correspondences_ [private]

Minimum number of correspondences for ICP to contuinue.

Definition at line 93 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::model_idx_ [private]

Current intex in the ring buffer.

Definition at line 131 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

PointCloudFeature::Ptr rgbdtools::MotionEstimationICPProbModel::model_ptr_ [private]

The model point cloud.

Definition at line 130 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::model_size_ [private]

Current model size.

Definition at line 132 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

KdTree rgbdtools::MotionEstimationICPProbModel::model_tree_ [private]

Kdtree of model_ptr_.

Definition at line 136 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

int rgbdtools::MotionEstimationICPProbModel::n_nearest_neighbors_ [private]

How many euclidean neighbors to go through, in a brute force search of the closest Mahalanobis neighbor.

Definition at line 98 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::tf_epsilon_angular_ [private]

Angular convergence criteria for ICP.

Definition at line 107 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

double rgbdtools::MotionEstimationICPProbModel::tf_epsilon_linear_ [private]

Linear convergence criteria for ICP.

Definition at line 106 of file include/rgbdtools/registration/motion_estimation_icp_prob_model.h.

---

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

• include/rgbdtools/registration/motion_estimation_icp_prob_model.h
• rgbdtools_git/include/rgbdtools/registration/motion_estimation_icp_prob_model.h
• motion_estimation_icp_prob_model.cpp