gazebo::sensors::GaussianNoiseModel Class Reference

Gaussian noise class. More...

#include <GaussianNoiseModel.hh>

Inheritance diagram for gazebo::sensors::GaussianNoiseModel:

Collaboration diagram for gazebo::sensors::GaussianNoiseModel:

Public Member Functions
	GaussianNoiseModel ()
	Constructor. More...
virtual	~GaussianNoiseModel ()
	Destructor. More...
double	ApplyImpl (double _in)
	Apply noise to input data value. More...
virtual void	Fini ()
	Finalize the noise model. More...
double	GetBias () const
	Accessor for bias. More...
double	GetMean () const
	Accessor for mean. More...
double	GetStdDev () const
	Accessor for stddev. More...
virtual void	Load (sdf::ElementPtr _sdf)
	Load noise parameters from sdf. More...
Public Member Functions inherited from gazebo::sensors::Noise
	Noise (NoiseType _type)
	Constructor. More...
virtual	~Noise ()
	Destructor. More...
double	Apply (double _in)
	Apply noise to input data value. More...
NoiseType	GetNoiseType () const
	Accessor for NoiseType. More...
virtual void	SetCamera (rendering::CameraPtr _camera)
	Set camera needed to create image noise. More...
virtual void	SetCustomNoiseCallback (boost::function< double(double)> _cb)
	Register a custom noise callback. More...

Protected Attributes
double	bias
	If type starts with GAUSSIAN, the bias we'll add. More...
double	mean
	If type starts with GAUSSIAN, the mean of the distribution from which we sample when adding noise. More...
double	precision
	If type==GAUSSIAN_QUANTIZED, the precision to which the output signal is rounded. More...
bool	quantized
	True if the type is GAUSSIAN_QUANTIZED. More...
double	stdDev
	If type starts with GAUSSIAN, the standard deviation of the distribution from which we sample when adding noise. More...

Additional Inherited Members
Public Types inherited from gazebo::sensors::Noise
enum	NoiseType { NONE, CUSTOM, GAUSSIAN }
	Which noise types we support. More...

Detailed Description

Gaussian noise class.

Gaussian noise class for image sensors.

Constructor & Destructor Documentation

gazebo::sensors::GaussianNoiseModel::GaussianNoiseModel

(

)

Constructor.

virtual gazebo::sensors::GaussianNoiseModel::~GaussianNoiseModel ( )

virtual

Destructor.

Member Function Documentation

double gazebo::sensors::GaussianNoiseModel::ApplyImpl ( double  _in )

virtual

Apply noise to input data value.

This gets overriden by derived classes, and called by Apply.

Parameters

[in]

_in

Input data value.

Returns

Data with noise applied.

Reimplemented from gazebo::sensors::Noise.

virtual void gazebo::sensors::GaussianNoiseModel::Fini ( )

virtual

Finalize the noise model.

Reimplemented from gazebo::sensors::Noise.

Reimplemented in gazebo::sensors::ImageGaussianNoiseModel.

double gazebo::sensors::GaussianNoiseModel::GetBias

(

)

const

Accessor for bias.

Returns

Bias on output.

double gazebo::sensors::GaussianNoiseModel::GetMean

(

)

const

Accessor for mean.

Returns

Mean of Gaussian noise.

double gazebo::sensors::GaussianNoiseModel::GetStdDev

(

)

const

Accessor for stddev.

Returns

Standard deviation of Gaussian noise.

virtual void gazebo::sensors::GaussianNoiseModel::Load ( sdf::ElementPtr  _sdf )

virtual

Load noise parameters from sdf.

Parameters

[in]	_sdf	SDF parameters.
[in]	_sensor	Type of sensor.

Reimplemented from gazebo::sensors::Noise.

Reimplemented in gazebo::sensors::ImageGaussianNoiseModel.

Member Data Documentation

double gazebo::sensors::GaussianNoiseModel::bias

protected

If type starts with GAUSSIAN, the bias we'll add.

double gazebo::sensors::GaussianNoiseModel::mean

protected

If type starts with GAUSSIAN, the mean of the distribution from which we sample when adding noise.

double gazebo::sensors::GaussianNoiseModel::precision

protected

If type==GAUSSIAN_QUANTIZED, the precision to which the output signal is rounded.

bool gazebo::sensors::GaussianNoiseModel::quantized

protected

True if the type is GAUSSIAN_QUANTIZED.

double gazebo::sensors::GaussianNoiseModel::stdDev

protected

If type starts with GAUSSIAN, the standard deviation of the distribution from which we sample when adding noise.

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

• GaussianNoiseModel.hh