InvertMotorSpace Class Reference

class for robot controller that uses the georg's matrixlib for direct matrix inversion for n channels (simple one layer networks) More...

#include <invertmotorspace.h>

Inherits InvertMotorController.

Inheritance diagram for InvertMotorSpace:

[legend]Collaboration diagram for InvertMotorSpace:

[legend]List of all members.


Public Member Functions
	InvertMotorSpace (int buffersize, double cInit=0.1, bool someInternalParams=true)
virtual void	init (int sensornumber, int motornumber)
	initialisation of the controller with the given sensor/ motornumber Must be called before use.
virtual	~InvertMotorSpace ()
virtual int	getSensorNumber () const
	returns the number of sensors the controller was initialised with or 0 if not initialised
virtual int	getMotorNumber () const
	returns the mumber of motors the controller was initialised with or 0 if not initialised
virtual void	step (const sensor , int number_sensors, motor , int number_motors)
	performs one step (includes learning).
virtual void	stepNoLearning (const sensor , int number_sensors, motor , int number_motors)
	performs one step without learning. Calulates motor commands from sensor inputs.
virtual bool	store (FILE *f) const
	stores the controller values to a given file (binary).
virtual bool	restore (FILE *f)
	loads the controller values from a given file (binary).
virtual std::list< iparamkey >	getInternalParamNames () const
	The list of the names of all internal parameters given by getInternalParams().
virtual std::list< iparamval >	getInternalParams () const
virtual std::list< ILayer >	getStructuralLayers () const
	Specifies which parameter vector forms a structural layer (in terms of a neural network) The ordering is important.
virtual std::list< IConnection >	getStructuralConnections () const
	Specifies which parameter matrix forms a connection between layers (in terms of a neural network) The orderning is not important.
Protected Member Functions
void	fillBuffersAndControl (const sensor x_, int number_sensors, motor y_, int number_motors)
	puts the sensors in the ringbuffer, generate controller values and put them in the
virtual void	learnController (const matrix::Matrix &x, const matrix::Matrix &x_smooth, int delay)
	learn h,C, delayed motors y and corresponding sensors x
virtual void	learnModel (const matrix::Matrix &x, const matrix::Matrix &y)
	learn A, using motors y and corresponding sensors x
virtual matrix::Matrix	calculateControllerValues (const matrix::Matrix &x_smooth)
	returns controller output for given sensor values
Protected Attributes
unsigned short	number_sensors
unsigned short	number_motors
matrix::Matrix	A
matrix::Matrix	C
matrix::Matrix	R
matrix::Matrix	H
matrix::Matrix	B
NoiseGenerator *	BNoiseGen
matrix::Matrix *	x_buffer
matrix::Matrix *	y_buffer
matrix::Matrix	x_smooth
bool	someInternalParams
double	cInit

Detailed Description

class for robot controller that uses the georg's matrixlib for direct matrix inversion for n channels (simple one layer networks)

Implements standart parameters: eps, rho, mu, stepnumber4avg, stepnumber4delay

Examples:: directconnect/directconnect.cpp, integration/main.cpp, and main.cpp.

Constructor & Destructor Documentation

InvertMotorSpace ( int buffersize,

double cInit = 0.1,

bool someInternalParams = true

)

~InvertMotorSpace ( ) [virtual]

Member Function Documentation

Matrix calculateControllerValues ( const matrix::Matrix & x_smooth ) [protected, virtual]

returns controller output for given sensor values

Parameters:

x_smooth smoothed sensors Matrix(number_channels,1)

void fillBuffersAndControl ( const sensor * x_,

int number_sensors,

motor * y_,

int number_motors

) [protected]

puts the sensors in the ringbuffer, generate controller values and put them in the

list< Inspectable::iparamkey > getInternalParamNames ( ) const [virtual]

The list of the names of all internal parameters given by getInternalParams().
The naming convention is "v[i]" for vectors and "A[i][j]" for matrices, where i, j start at 0.
Returns:
: list of keys

Implements Inspectable.

list< Inspectable::iparamval > getInternalParams ( ) const [virtual]

Returns:
: list of values

Implements Inspectable.

virtual int getMotorNumber ( ) const [inline, virtual]

returns the mumber of motors the controller was initialised with or 0 if not initialised

Reimplemented from AbstractController.

virtual int getSensorNumber ( ) const [inline, virtual]

returns the number of sensors the controller was initialised with or 0 if not initialised

Reimplemented from AbstractController.

list< Inspectable::IConnection > getStructuralConnections ( ) const [virtual]

Specifies which parameter matrix forms a connection between layers (in terms of a neural network) The orderning is not important.

Returns:
: list of layer names with dimension

Reimplemented from Inspectable.

list< Inspectable::ILayer > getStructuralLayers ( ) const [virtual]

Specifies which parameter vector forms a structural layer (in terms of a neural network) The ordering is important.
The first entry is the input layer and so on.
Returns:
: list of layer names with dimension

Reimplemented from Inspectable.

void init ( int sensornumber,

int motornumber

) [virtual]

initialisation of the controller with the given sensor/ motornumber Must be called before use.

Reimplemented from AbstractController.

void learnController ( const matrix::Matrix & x,

const matrix::Matrix & x_smooth,

int delay

) [protected, virtual]

learn h,C, delayed motors y and corresponding sensors x

void learnModel ( const matrix::Matrix & x,

const matrix::Matrix & y

) [protected, virtual]

learn A, using motors y and corresponding sensors x

bool restore ( FILE * f ) [virtual]

loads the controller values from a given file (binary).

Implements Storeable.

void step ( const sensor * ,

int number_sensors,

motor * ,

int number_motors

) [virtual]

performs one step (includes learning).
Calulates motor commands from sensor inputs.
Reimplemented from AbstractController.

void stepNoLearning ( const sensor * ,

int number_sensors,

motor * ,

int number_motors

) [virtual]

performs one step without learning. Calulates motor commands from sensor inputs.

Reimplemented from AbstractController.