/home/laradmin/lar/perception/planarobstacles/mtt/include/mtt/mtt_kalman.h File Reference

Kalman estimation related functions header. More...

#include "mtt_common.h"

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Functions
void	AddPointPath (t_path *path, double x, double y)
void	AllocMotionModels (t_list &list, t_config &config)
CvKalman *	CreateModelCTRV (void)
CvKalman *	CreateModelCV (void)
CvKalman *	CreateModelCV_SC (void)
CvKalman *	CreateModelFwdCt (void)
void	dA_FwdCt (CvKalman *model, double q[6], double dt, double l=2.54)
void	dH_FwdCt (CvKalman *model)
void	GetErrorConvariance (t_errors *error)
	Get covariance.
void	IterateMotionModelCTRV (CvKalman *model, double vm, double wm)
void	IterateMotionModelCV (CvKalman *model, double vxm, double vym)
double	IterateMotionModelCV_SC (CvKalman *model, double vm)
void	IterateMotionModelFwdCt (CvKalman *model, double z[2])
void	MotionModelsIteration (vector< t_listPtr > &list, t_config &config)
double	point2line_distance (double alpha, double ro, double x, double y)
	Calculates the line to point distance.
int	real2print (double x, t_config *config)
void	SetSearchArea (t_list &list, t_config &config)
void	UpdateTransitionMatrixCTRV (CvKalman *model, double, double, double t, double v, double w, double dt)
void	UpdateTransitionMatrixCV (CvKalman *model, double dt)
void	UpdateTransitionMatrixCV_SC (CvKalman *model, double dt)
Variables
FILE *	fp
double	grxy
double	s [6]
int	select_object
double	theta
double	vel

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Detailed Description

Kalman estimation related functions header.

Definition in file mtt_kalman.h.

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Function Documentation

void AddPointPath	(	t_path *	path,
		double	x,
		double	y
	)

Definition at line 319 of file mtt_association.cpp.

void AllocMotionModels	(	t_list &	list,
		t_config &	config
	)

Definition at line 415 of file mtt_kalman.cpp.

CvKalman* CreateModelCTRV

(

void

)

Definition at line 637 of file mtt_kalman.cpp.

CvKalman* CreateModelCV

(

void

)

Definition at line 705 of file mtt_kalman.cpp.

CvKalman* CreateModelCV_SC

(

void

)

Definition at line 673 of file mtt_kalman.cpp.

CvKalman* CreateModelFwdCt

(

void

)

Definition at line 756 of file mtt_kalman.cpp.

void dA_FwdCt	(	CvKalman *	model,
		double	q[6],
		double	dt,
		double	l = 2.54
	)

Definition at line 1036 of file mtt_kalman.cpp.

void dH_FwdCt

(

CvKalman *

model

)

Definition at line 1025 of file mtt_kalman.cpp.

void GetErrorConvariance

(

t_errors *

error

)

Get covariance.

Returns:

void

Initalise auxiliar matrixes

Set accumulators to 0

Do Cov(Innovation) = 1/m * S(i=0,i< m-1,d[k-i]*d[k-i]') and Cov(Residue) = 1/m * S(i=0,i< m-1,e[k-i]*e[k-i]')

Todo:

Wend the number of points is growing the covariance is way to big, i don't realy know why

Definition at line 507 of file mtt_kalman.cpp.

void IterateMotionModelCTRV	(	CvKalman *	model,
		double	vm,
		double	wm
	)

Definition at line 779 of file mtt_kalman.cpp.

void IterateMotionModelCV	(	CvKalman *	model,
		double	vxm,
		double	vym
	)

Definition at line 912 of file mtt_kalman.cpp.

double IterateMotionModelCV_SC	(	CvKalman *	model,
		double	vm
	)

Definition at line 873 of file mtt_kalman.cpp.

void IterateMotionModelFwdCt	(	CvKalman *	model,
		double	z[2]
	)

Definition at line 841 of file mtt_kalman.cpp.

void MotionModelsIteration	(	vector< t_listPtr > &	list,
		t_config &	config
	)

If the object is new, we set the prestate and poststate, given that this is not a new measurement, of the filter to the current measurement

Get the new measurement into the filter and correct, t=k

Extract the correct state from the filter and put it to path[k]

After correction iterate the filter to make a prediction, t=k+1

Extract the prediction from the filter

Obtain error vectors

Add estimated point to path

Put velocity into data file

Obtain velocity

Put lateral error into data file

Put error cov and AKF gains into data file

Define a new search area based on the kalman errors and predicted position

Do some tweaks on the kalman errors

* Update white noise scale **************************/

Only update if the object is visible

Definition at line 64 of file mtt_kalman.cpp.

double point2line_distance	(	double	alpha,
		double	ro,
		double	x,
		double	y
	)

Calculates the line to point distance.

Parameters:

	alpha	polar coordinates of the line
	ro	polar coordinates of the line
	x	cartesian coordinates of the point
	y

Returns:

algebric distance

Definition at line 65 of file line_fitting.cpp.

int real2print	(	double	x,
		t_config *	config
	)

void SetSearchArea	(	t_list &	list,
		t_config &	config
	)

Small bonus to new objects

Todo:

I should use a equation that allowed a more soft transition

Definition at line 252 of file mtt_association.cpp.

void UpdateTransitionMatrixCTRV	(	CvKalman *	model,
		double	,
		double	,
		double	t,
		double	v,
		double	w,
		double	dt
	)

Definition at line 1155 of file mtt_kalman.cpp.

void UpdateTransitionMatrixCV	(	CvKalman *	model,
		double	dt
	)

Definition at line 974 of file mtt_kalman.cpp.

void UpdateTransitionMatrixCV_SC	(	CvKalman *	model,
		double	dt
	)

Definition at line 954 of file mtt_kalman.cpp.

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Variable Documentation

FILE* fp

double grxy

double s[6]

int select_object

Definition at line 36 of file mtt_kalman.cpp.

double theta

double vel