[Bayes++] Bayes++ to predict robots location

[Vinh <arb...@go...>]

Hi,
I'm just started playing around with the bayes++ library to accomplish
following task:

A vision system provides me with the position of our robot on the
ground (2d). In addition, I want to merge this information with the
internal wheelencoders (giving me the speed and rotation of the robot)
to get an estimate of the position of the robot.
Since the robot is rotating as well the system model is not linear.
First I thought of using a particle filter to get the estimate, but
that probably would be overkill, making the system slower than needed
since the underlying probability distribution could simply be one
gaussian.
I had a look at the PV example, but got stucked and would like to ask
for advice.

In the state prediction (Linear_predict_model), there is something
looking like this:

	q[0] = dt*sqr((1-Fvv)*V_NOISE);
	G(0,0) = 0.;
	G(1,0) = 1.;

Can I leave it like that if I assume that the noise is always constant?

Since the motion/prediction model is not linear due to the rotation,
what would I need to change to modify it so that the filter can deal
with non-linearities?

Thanks very much for your help!!

Vinh