KalmanFilterHarness.cpp File Reference

---

Detailed Description

Basic test of KalmanFilter.

This test sets up a linear model for testing the Kalman filter implementation. For comparison against an existing implementation, the Bayesian Filtering Library (http://www.orocos.org/bfl), the model used is identical to that described in that particularly library's tutorial (http://people.mech.kuleuven.be/~tdelaet/getting_started_guide/).

Results are output into files as follows:

results/KalmanFilterHarness_actual.out

Actual state of the robot at each time. Columns are as follows:

• time
• x coordinate
• y coordinate
• orientation (radians)

results/KalmanFilterHarness_meas.out

Measurement at each time step. Columns are as follows:

• time
• measurement

results/KalmanFilterHarness_pred.out

Predicted state at each time step. Columns are as follows:

• time
• mean x coordinate
• mean y coordinate
• mean orientation
• The remaining columns give the covariance matrix between the above state variables.

Results

Results are as follows:

Results, c.f. BFL Tutorial Figures 3.2 and 3.3

Definition in file KalmanFilterHarness.cpp.

Go to the source code of this file.

Namespaces
namespace	std
namespace	indii::ml::filter
Defines
#define	STATE_SIZE   5
#define	MEAS_SIZE   1
#define	ACTUAL_SIZE   3
#define	STEPS   100
Functions
void	outputVector (ofstream &out, aux::vector vec)
void	outputMatrix (ofstream &out, aux::matrix mat)
int	main (int argc, const char *argv)
	Run tests.

---

Function Documentation

int main	(	int	argc,
		const char *	argv
	)

Run tests.

Definition at line 78 of file KalmanFilterHarness.cpp.

---