Represents a cluster of 3D points using PCL (Point Cloud Library). More...

#include <cluster.hpp>

Collaboration diagram for Cluster:

Public Member Functions
	Cluster (const sensor_msgs::msg::PointCloud2::SharedPtr &point_cloud, const std::vector< int > &point_indices)
	Constructor for the Cluster class.

Eigen::Vector4f	get_centroid ()
	Get the centroid of the cluster.

Eigen::Vector4f	get_center (Plane &plane)
	Get the Center of the cone's cluster.

std::string	get_color ()
	Get the color associated with the cluster.

void	set_color (const std::string &new_color)
	Set the color for the cluster.

void	set_point_indices (const std::vector< int > &new_point_indices)
	Set the Point Cloud data for the cluster.

const std::vector< int > &	get_point_indices ()
	Get the Point Cloud data of the cluster.

const sensor_msgs::msg::PointCloud2::SharedPtr &	get_point_cloud ()
	Get the Point Cloud data of the cluster.

void	set_confidence (double newConfidence)
	Set the Confidence of the cluster to be or not to be a cone.

double	get_confidence ()
	Get the Confidence of the cluster to be (or not to be) a cone.

void	set_z_score (double mean_x, double std_dev_x, double mean_y, double std_dev_y)
	Set the z score object on the x and y axis.

double	get_z_score_x () const
	Get the z score on x-axis of an object.

double	get_z_score_y () const
	Get the z score on y-axis of an object.

bool	get_is_large ()
	Get cluster's corresponding cone size.

void	set_is_large ()
	Set cluster as a contender for a large cone.

Static Public Member Functions
static std::tuple< double, double, double, double >	calculate_mean_and_std_dev (std::vector< Cluster > &clusters)
	Calculates the mean and standard deviation on x and y axis.

static void	set_z_scores (std::vector< Cluster > &clusters)
	Set the z scores object on every cluster of the vector.

Private Attributes
const sensor_msgs::msg::PointCloud2::SharedPtr	_point_cloud_
	Point cloud data for the cluster.

std::vector< int >	_point_indices_
	Indices of points in the cluster.

std::string	_color_ = "undefined"
	Color associated with the cluster.

Eigen::Vector4f	_centroid_
	Centroid of the cluster.

Eigen::Vector4f	_center_
	Center of the cone's cluster.

bool	_centroid_is_defined_ = false
	Flag indicating whether the centroid is defined or not.

bool	_center_is_defined_ = false
	Flag indicating whether the center is defined or not.

double	_confidence_ = 0
	Confidence on the cluster to be (or not) a cone.

double	_z_score_x_ = 0

double	_z_score_y_ = 0

bool	_is_large_ = false
	Flag indicating the size of the cluster :

Static Private Attributes
static constexpr auto	center_calculator
	Calculates the center of the cone.

static constexpr auto	centroid_calculator
	Calculates the centroid of the cluster.

Detailed Description

Represents a cluster of 3D points using PCL (Point Cloud Library).

Definition at line 14 of file cluster.hpp.

Constructor & Destructor Documentation

◆ Cluster()

Cluster::Cluster	(	const sensor_msgs::msg::PointCloud2::SharedPtr &	point_cloud,
		const std::vector< int > &	point_indices
	)

explicit

Constructor for the Cluster class.

Definition at line 3 of file cluster.cpp.

Member Function Documentation

◆ calculate_mean_and_std_dev()

std::tuple< double, double, double, double > Cluster::calculate_mean_and_std_dev ( std::vector< Cluster > & clusters )

static

Calculates the mean and standard deviation on x and y axis.

Parameters

clusters Clusters to apply get the statistical values

Returns: std::tuple<double, double, double, double> (mean x, mean y, standard deviation x, standard deviation y)

Definition at line 69 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_center()

Eigen::Vector4f Cluster::get_center ( Plane & plane )

Get the Center of the cone's cluster.

Returns: Eigen::Vector4f representing the center

Definition at line 18 of file cluster.cpp.

◆ get_centroid()

Eigen::Vector4f Cluster::get_centroid ( )

Get the centroid of the cluster.

Returns: Eigen::Vector4f representing the centroid.

Definition at line 7 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_color()

std::string Cluster::get_color ( )

Get the color associated with the cluster.

Returns: std::string representing the color.

Definition at line 30 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_confidence()

double Cluster::get_confidence ( )

Get the Confidence of the cluster to be (or not to be) a cone.

Returns: double Cluster's confidence

Definition at line 52 of file cluster.cpp.

◆ get_is_large()

bool Cluster::get_is_large ( )

Get cluster's corresponding cone size.

Returns: bool representing size .

Definition at line 101 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_point_cloud()

const sensor_msgs::msg::PointCloud2::SharedPtr & Cluster::get_point_cloud ( )

Get the Point Cloud data of the cluster.

Returns: pcl::PointCloud<pcl::PointXYZI>::Ptr representing the Point Cloud data.

Definition at line 46 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_point_indices()

const std::vector< int > & Cluster::get_point_indices ( )

Get the Point Cloud data of the cluster.

Returns: pcl::PointCloud<pcl::PointXYZI>::Ptr representing the Point Cloud data.

Definition at line 44 of file cluster.cpp.

Here is the caller graph for this function:

◆ get_z_score_x()

double Cluster::get_z_score_x ( ) const

Get the z score on x-axis of an object.

Returns: double Z-score on x axis

Definition at line 65 of file cluster.cpp.

◆ get_z_score_y()

double Cluster::get_z_score_y ( ) const

Get the z score on y-axis of an object.

Returns: double Z-score on y axis

Definition at line 67 of file cluster.cpp.

◆ set_color()

void Cluster::set_color ( const std::string & new_color )

Set the color for the cluster.

Parameters

new_color The new color to be set.

Definition at line 32 of file cluster.cpp.

Here is the caller graph for this function:

◆ set_confidence()

void Cluster::set_confidence ( double newConfidence )

Set the Confidence of the cluster to be or not to be a cone.

Parameters

newConfidence The new Confidence of the cluster

Definition at line 50 of file cluster.cpp.

◆ set_is_large()

void Cluster::set_is_large ( )

Set cluster as a contender for a large cone.

Definition at line 103 of file cluster.cpp.

Here is the caller graph for this function:

◆ set_point_indices()

void Cluster::set_point_indices ( const std::vector< int > & new_point_indices )

Set the Point Cloud data for the cluster.

Parameters

new_point_cloud Pointer to the new Point Cloud data.

Definition at line 38 of file cluster.cpp.

◆ set_z_score()

void Cluster::set_z_score	(	double	mean_x,
		double	std_dev_x,
		double	mean_y,
		double	std_dev_y
	)

Set the z score object on the x and y axis.

Parameters

mean_x	Mean of the x on the point's distribution
std_dev_x	Standard Deviation of the x on the point's distribution
mean_y	Mean of the y on the point's distribution
std_dev_y	Standard Deviation of the y on the point's distribution

Definition at line 54 of file cluster.cpp.

Here is the call graph for this function:

◆ set_z_scores()

void Cluster::set_z_scores ( std::vector< Cluster > & clusters )

static

Set the z scores object on every cluster of the vector.

Parameters

clusters Vector of clusters in which the a-scores will be applied individually

Definition at line 94 of file cluster.cpp.

Here is the call graph for this function:

Here is the caller graph for this function:

Member Data Documentation

◆ _center_

Eigen::Vector4f Cluster::_center_

private

Center of the cone's cluster.

Definition at line 137 of file cluster.hpp.

◆ _center_is_defined_

bool Cluster::_center_is_defined_ = false

private

Flag indicating whether the center is defined or not.

Definition at line 139 of file cluster.hpp.

◆ _centroid_

Eigen::Vector4f Cluster::_centroid_

private

Centroid of the cluster.

Definition at line 136 of file cluster.hpp.

◆ _centroid_is_defined_

bool Cluster::_centroid_is_defined_ = false

private

Flag indicating whether the centroid is defined or not.

Definition at line 138 of file cluster.hpp.

◆ _color_

std::string Cluster::_color_ = "undefined"

private

Color associated with the cluster.

Definition at line 135 of file cluster.hpp.

◆ _confidence_

double Cluster::_confidence_ = 0

private

Confidence on the cluster to be (or not) a cone.

Definition at line 140 of file cluster.hpp.

◆ _is_large_

bool Cluster::_is_large_ = false

private

Flag indicating the size of the cluster :

true = large cluster. false = small = cluster.

Definition at line 143 of file cluster.hpp.

◆ _point_cloud_

const sensor_msgs::msg::PointCloud2::SharedPtr Cluster::_point_cloud_

private

Point cloud data for the cluster.

Definition at line 133 of file cluster.hpp.

◆ _point_indices_

std::vector<int> Cluster::_point_indices_

private

Indices of points in the cluster.

Definition at line 134 of file cluster.hpp.

◆ _z_score_x_

double Cluster::_z_score_x_ = 0

private

Definition at line 141 of file cluster.hpp.

◆ _z_score_y_

double Cluster::_z_score_y_ = 0

private

Definition at line 142 of file cluster.hpp.

◆ center_calculator

constexpr auto Cluster::center_calculator

staticconstexprprivate

Initial value:

=

CircunferenceCenterCalculator()

CircunferenceCenterCalculator

Concrete class representing a circumference-based method for estimating the center position of a cone...

Definition circunference_center_calculation.hpp:15

Calculates the center of the cone.

Definition at line 147 of file cluster.hpp.

◆ centroid_calculator

constexpr auto Cluster::centroid_calculator

staticconstexprprivate

Initial value:

=

CentroidCalculator()

CentroidCalculator

Concrete Class representing a centroid-based method for estimating the center position of a cone.

Definition centroid_calculation.hpp:11

Calculates the centroid of the cluster.

Definition at line 149 of file cluster.hpp.

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

src/perception/include/utils/cluster.hpp
src/perception/src/utils/cluster.cpp

Public Member Functions

Static Public Member Functions

Private Attributes

Static Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ Cluster()

Member Function Documentation

◆ calculate_mean_and_std_dev()

◆ get_center()

◆ get_centroid()

◆ get_color()

◆ get_confidence()

◆ get_is_large()

◆ get_point_cloud()

◆ get_point_indices()

◆ get_z_score_x()

◆ get_z_score_y()

◆ set_color()

◆ set_confidence()

◆ set_is_large()

◆ set_point_indices()

◆ set_z_score()

◆ set_z_scores()

Member Data Documentation

◆ _center_

◆ _center_is_defined_

◆ _centroid_

◆ _centroid_is_defined_

◆ _color_

◆ _confidence_

◆ _is_large_

◆ _point_cloud_

◆ _point_indices_

◆ _z_score_x_

◆ _z_score_y_

◆ center_calculator

◆ centroid_calculator