InvertMotorBigModel Class Reference

class for robot controller is based on InvertMotorNStep More...

#include <invertmotorbigmodel.h>

Inheritance diagram for InvertMotorBigModel:

[legend]Collaboration diagram for InvertMotorBigModel:


Public Member Functions
	InvertMotorBigModel (const InvertMotorBigModelConf &conf=getDefaultConf())
virtual void	init (int sensornumber, int motornumber)
	initialisation of the controller with the given sensor/ motornumber Must be called before use.
virtual	~InvertMotorBigModel ()
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.
virtual bool	restore (FILE *f)
	loads the controller values from a given file.
virtual iparamkeylist	getInternalParamNames () const
	The list of the names of all internal parameters given by getInternalParams().
virtual iparamvallist	getInternalParams () const
virtual ilayerlist	getStructuralLayers () const
	Specifies which parameter vector forms a structural layer (in terms of a neural network) The ordering is important.
virtual iconnectionlist	getStructuralConnections () const
	Specifies which parameter matrix forms a connection between layers (in terms of a neural network) The orderning is not important.
virtual paramval	getParam (const paramkey &key) const
	returns the value of the requested parameter or 0 (+ error message to stderr) if unknown.
virtual bool	setParam (const paramkey &key, paramval val)
	sets the value of the given parameter or does nothing if unknown.
virtual paramlist	getParamList () const
	The list of all parameters with there value as allocated lists.
virtual void	setTeachingMode (bool onOff)
virtual bool	getTeachingMode ()
virtual void	setMotorTeachingSignal (const motor *teaching, int len)
void	calcCandHUpdatesTeaching (matrix::Matrix &C_update, matrix::Matrix &H_update, int y_delay)
	calculates the Update for C and H using the teaching signal
void	getLastMotors (motor *motors, int len)
Static Public Member Functions
InvertMotorBigModelConf	getDefaultConf ()
Protected Member Functions
virtual 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	calcEtaAndBufferIt (int delay)
	calculates the first shift into the motor space useing delayed motor values.
virtual void	learnController ()
	learn H,C with motors y and corresponding sensors x
virtual void	calcCandHUpdates (matrix::Matrix &C_update, matrix::Matrix &H_update, int y_delay)
	calculates the Update for C and H
virtual void	updateCandH (const matrix::Matrix &C_update, const matrix::Matrix &H_update, double squashSize)
	updates the matrix C and H
virtual void	learnModel (int delay)
	learn A, (and S) using motors y and corresponding sensors x
virtual matrix::Matrix	calculateControllerValues (const matrix::Matrix &x_smooth)
	returns controller output for given sensor values
virtual double	calcErrorFactor (const matrix::Matrix &e, bool loga, bool root)
	calculates the error_factor for either logarithmic (E=ln(e^Te)) or square (E=sqrt(e^te)) error
Protected Attributes
unsigned short	number_sensors
unsigned short	number_motors
matrix::Matrix	A
	current response function of the model
matrix::Matrix	C
	Controller Matrix.
matrix::Matrix	H
	Controller Bias.
matrix::Matrix	R
	C*A.
matrix::Matrix	SmallID
	small identity matrix in the dimension of R
matrix::Matrix	xsi
	current output error
double	xsi_norm
	norm of matrix
double	xsi_norm_avg
	average norm of xsi (used to define whether Modell learns)
double	pain
	if the modelling error (xsi) is too high we have a pain signal
matrix::Matrix *	x_buffer
matrix::Matrix *	y_buffer
matrix::Matrix *	eta_buffer
matrix::Matrix	zero_eta
matrix::Matrix	x_smooth
matrix::Matrix	y_teaching
	teaching motor signal
InvertMotorBigModelConf	conf

Detailed Description

class for robot controller is based on InvertMotorNStep

direct inversion

motor space

multilayer,nonlinear model

Constructor & Destructor Documentation

InvertMotorBigModel ( const InvertMotorBigModelConf & conf = getDefaultConf() )

~InvertMotorBigModel ( ) [virtual]

Member Function Documentation

void calcCandHUpdates ( matrix::Matrix & C_update,

matrix::Matrix & H_update,

int y_delay

) [protected, virtual]

calculates the Update for C and H

void calcCandHUpdatesTeaching ( matrix::Matrix & C_update,

matrix::Matrix & H_update,

int y_delay

)

calculates the Update for C and H using the teaching signal

double calcErrorFactor ( const matrix::Matrix & e,

bool loga,

bool root

) [protected, virtual]

calculates the error_factor for either logarithmic (E=ln(e^T*e)) or square (E=sqrt(e^t*e)) error

Reimplemented from InvertMotorController.

void calcEtaAndBufferIt ( int delay ) [protected, virtual]

calculates the first shift into the motor space useing delayed motor values.

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, virtual]

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

InvertMotorBigModelConf getDefaultConf ( ) [inline, static]

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.

void getLastMotors ( motor * motors,

int len

)

virtual int getMotorNumber ( ) const [inline, virtual]

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

Reimplemented from AbstractController.

Configurable::paramval getParam ( const paramkey & key ) const [virtual]

returns the value of the requested parameter or 0 (+ error message to stderr) if unknown.

Reimplemented from InvertMotorController.

Configurable::paramlist getParamList ( ) const [virtual]

The list of all parameters with there value as allocated lists.

Returns:
list of key-value pairs

Reimplemented from InvertMotorController.

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.

bool getTeachingMode ( ) [virtual]

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 ( ) [protected, virtual]

learn H,C with motors y and corresponding sensors x

void learnModel ( int delay ) [protected, virtual]

learn A, (and S) using motors y and corresponding sensors x

bool restore ( FILE * f ) [virtual]

loads the controller values from a given file.

Implements Storeable.

void setMotorTeachingSignal ( const motor * teaching,

int len

) [virtual]

bool setParam ( const paramkey & key,

paramval val

) [virtual]

sets the value of the given parameter or does nothing if unknown.

Reimplemented from InvertMotorController.

void setTeachingMode ( bool onOff ) [virtual]

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.

bool store ( FILE * f ) const [virtual]

stores the controller values to a given file.

Implements Storeable.

void updateCandH ( const matrix::Matrix & C_update,

const matrix::Matrix & H_update,

double squashSize

) [protected, virtual]

updates the matrix C and H