KalmanFixedPositionModel Class Reference

Contains a KalmanBallLocator process model for non-moving balls. More...

#include <FixedPositionModel.h>

Inheritance diagram for KalmanFixedPositionModel:

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[legend]List of all members.

Public Member Functions
	KalmanFixedPositionModel ()
virtual	~KalmanFixedPositionModel ()
virtual const char *	getModelName () const
	Returns the name of the process model.
virtual int	getStateDim () const
	Returns the dimension of the state.
virtual void	getP (double *pDest) const
	Retrieves the internal kalman filter covariance matrix.
virtual void	getQ (double *pDest) const
	Retrieves the process error covariance matrix.
virtual void	setQ (const double *pSource)
	Sets the process error covariance matrix.
virtual void	getR (double *pDest) const
	Retrieves the measurement error covariance matrix.
virtual void	setR (double *pSource)
	Sets the measurement error covariance matrix.
virtual void	reset ()
	Resets the process model.
virtual KalmanUpdateResult	update (double time, double x, double y)
virtual KalmanPredictResult	predict (double time)
	Permorms a prediction of the ball state.
virtual void	adapt (const OdometryData &lastOdometry, const OdometryData &actualOdometry)
	Function to adapt the state of the model when position and rotation of the robot changes.
Private Attributes
Vector_n< double, 2 >	x_act
	Actual state: x_act[0] is x-position in meters x_act[1] is y-position in meters.
Matrix_nxn< double, 2 >	A
	linear process model matrix
Matrix_nxn< double, 2 >	P
	internal covariance matrix
Matrix_nxn< double, 2 >	Q
	process model error covariance matrix
Matrix_nxn< double, 2 >	R
	measurement error covariance matrix
bool	inited
	true, if model is initied
double	lastLiklihood
	last liklihood
double	lastTime
	last time in seconds
Vector_n< double, 2 >	x_minus
Matrix_nxn< double, 2 >	P_minus
Matrix_nxn< double, 2 >	C
Matrix_nxn< double, 2 >	C_inv
Matrix_nxn< double, 2 >	K
Vector_n< double, 2 >	z
Vector_n< double, 2 >	x_predict
Matrix_nxn< double, 2 >	globQ
	global process covariance matrix that is adapted with dt
Matrix_nxn< double, 2 >	globR
	global measurement covariance matrix
Static Private Attributes
double	defaultA [4]
	default linear process model matrix
double	defaultP [4]
	default internal covariance matrix
double	defaultQ [4]
	default process error covariance matrix
double	defaultR [4]
	default measurement error covariance matrix

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Detailed Description

Contains a KalmanBallLocator process model for non-moving balls.

Definition at line 19 of file FixedPositionModel.h.

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Constructor & Destructor Documentation

KalmanFixedPositionModel::KalmanFixedPositionModel (   )

Definition at line 34 of file FixedPositionModel.cpp. References defaultA, defaultQ, defaultR, and reset().

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KalmanFixedPositionModel::~KalmanFixedPositionModel (   )  [virtual]

Definition at line 42 of file FixedPositionModel.cpp.

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Member Function Documentation

virtual const char* KalmanFixedPositionModel::getModelName (   )  const [inline, virtual]

Returns the name of the process model. Returns: name of process model Implements KalmanProcessModelBase. Definition at line 26 of file FixedPositionModel.h.

virtual int KalmanFixedPositionModel::getStateDim (   )  const [inline, virtual]

Returns the dimension of the state. Returns: dimension of the state Implements KalmanProcessModelBase. Definition at line 28 of file FixedPositionModel.h.

virtual void KalmanFixedPositionModel::getP (  double *  pDest  )  const [inline, virtual]

Retrieves the internal kalman filter covariance matrix. Parameters: pDest  destination to store the covariance matrix to Implements KalmanProcessModelBase. Definition at line 29 of file FixedPositionModel.h. References Matrix_nxn< double, 2 >::copyTo().

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virtual void KalmanFixedPositionModel::getQ (  double *  pDest  )  const [inline, virtual]

Retrieves the process error covariance matrix. Parameters: pDest  destination to store the covariance matrix to Implements KalmanProcessModelBase. Definition at line 30 of file FixedPositionModel.h. References Matrix_nxn< double, 2 >::copyTo().

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virtual void KalmanFixedPositionModel::setQ (  const double *  pSource  )  [inline, virtual]

Sets the process error covariance matrix. Parameters: pSource  array containing the covariance matrix entries Implements KalmanProcessModelBase. Definition at line 31 of file FixedPositionModel.h.

virtual void KalmanFixedPositionModel::getR (  double *  pDest  )  const [inline, virtual]

Retrieves the measurement error covariance matrix. Parameters: pDest  destination to store the covariance matrix to Implements KalmanProcessModelBase. Definition at line 32 of file FixedPositionModel.h. References Matrix_nxn< double, 2 >::copyTo().

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virtual void KalmanFixedPositionModel::setR (  double *  pSource  )  [inline, virtual]

Sets the measurement error covariance matrix. Parameters: pSource  array containing the covariance matrix entries Implements KalmanProcessModelBase. Definition at line 33 of file FixedPositionModel.h.

void KalmanFixedPositionModel::reset (   )  [virtual]

Resets the process model. Implements KalmanProcessModelBase. Definition at line 46 of file FixedPositionModel.cpp. References defaultP, and inited. Referenced by KalmanFixedPositionModel(), predict(), and update().

KalmanUpdateResult KalmanFixedPositionModel::update (  double  time, double  x, double  y )  [virtual]

Definition at line 57 of file FixedPositionModel.cpp. References det(), Matrix_nxn< double, 2 >::eye(), MVTools::getMaxExpDouble(), idText, inited, invert(), MVTools::isNearZero(), KalmanUpdateResult::liklihood, OUTPUT, KalmanProcessModelBase::OutputException(), KalmanProcessModelBase::pi, reset(), KalmanUpdateResult::state, transpose(), KalmanBallState::vx, KalmanBallState::vy, KalmanBallState::x, and KalmanBallState::y.

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KalmanPredictResult KalmanFixedPositionModel::predict (  double  time  )  [virtual]

Permorms a prediction of the ball state. Parameters: time  actual time in seconds Returns: the predict results of the process model Implements KalmanProcessModelBase. Definition at line 185 of file FixedPositionModel.cpp. References inited, KalmanPredictResult::liklihood, KalmanProcessModelBase::OutputException(), reset(), KalmanPredictResult::state, KalmanBallState::vx, KalmanBallState::vy, KalmanBallState::x, and KalmanBallState::y.

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void KalmanFixedPositionModel::adapt (  const OdometryData &  lastOdometry, const OdometryData &  actualOdometry )  [virtual]

Function to adapt the state of the model when position and rotation of the robot changes. Parameters: lastOdometry  last odometry of robot (original values in millimeters are used) actualOdometry  actual odometry of robot (original values in millimeters are used) Implements KalmanProcessModelBase. Definition at line 215 of file FixedPositionModel.cpp. References Vector2< V >::x, and Vector2< V >::y.

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Member Data Documentation

Vector_n<double, 2> KalmanFixedPositionModel::x_act [private]

Actual state: x_act[0] is x-position in meters x_act[1] is y-position in meters. Definition at line 48 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::A [private]

linear process model matrix Definition at line 49 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::P [private]

internal covariance matrix Definition at line 50 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::Q [private]

process model error covariance matrix Definition at line 51 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::R [private]

measurement error covariance matrix Definition at line 52 of file FixedPositionModel.h.

bool KalmanFixedPositionModel::inited [private]

true, if model is initied Definition at line 54 of file FixedPositionModel.h. Referenced by predict(), reset(), and update().

double KalmanFixedPositionModel::lastLiklihood [private]

last liklihood Definition at line 55 of file FixedPositionModel.h.

double KalmanFixedPositionModel::lastTime [private]

last time in seconds Definition at line 56 of file FixedPositionModel.h.

Vector_n<double, 2> KalmanFixedPositionModel::x_minus [private]

Definition at line 59 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::P_minus [private]

Definition at line 60 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::C [private]

Definition at line 61 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::C_inv [private]

Definition at line 62 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::K [private]

Definition at line 63 of file FixedPositionModel.h.

Vector_n<double, 2> KalmanFixedPositionModel::z [private]

Definition at line 64 of file FixedPositionModel.h.

Vector_n<double, 2> KalmanFixedPositionModel::x_predict [private]

Definition at line 65 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::globQ [private]

global process covariance matrix that is adapted with dt Definition at line 68 of file FixedPositionModel.h.

Matrix_nxn<double, 2> KalmanFixedPositionModel::globR [private]

global measurement covariance matrix Definition at line 70 of file FixedPositionModel.h.

double KalmanFixedPositionModel::defaultA [static, private]

Initial value: { 1.0, 0.0, 0.0, 1.0 } default linear process model matrix Definition at line 7 of file FixedPositionModel.cpp. Referenced by KalmanFixedPositionModel().

double KalmanFixedPositionModel::defaultP [static, private]

Initial value: { 1.0, 0.0, 0.0, 1.0 } default internal covariance matrix Definition at line 13 of file FixedPositionModel.cpp. Referenced by reset().

double KalmanFixedPositionModel::defaultQ [static, private]

Initial value: { 0.01*0.01, 0.00*0.00, 0.00*0.00, 0.01*0.01 } default process error covariance matrix Definition at line 21 of file FixedPositionModel.cpp. Referenced by KalmanFixedPositionModel().

double KalmanFixedPositionModel::defaultR [static, private]

Initial value: { 0.04*0.04, 0.00*0.00, 0.00*0.00, 0.04*0.04 } default measurement error covariance matrix Definition at line 28 of file FixedPositionModel.cpp. Referenced by KalmanFixedPositionModel().

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

• Modules/BallLocator/GT2004ProcessModels/FixedPositionModel.h
• Modules/BallLocator/GT2004ProcessModels/FixedPositionModel.cpp

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