Re: [Bayes++] EKF bayes++ questions

[Nicola B. <nb...@es...>]

On Monday 01 May 2006 21:05, Jack Collier wrote:
> 1.  It appears as though I should be using the Covariance_scheme.  Is
> this correct?

Yes it is.

>
> 2.  My state prediction model is as follows:
>
> 	x' = x + (-(v/w)*sin(b) + (v/w)*sin(b+w*dt))
> 	y' = y + ((v/w)*cos(b) - (v/w)*cos(b+w*dt))
> 	theta' = theta + (w*dt)
>
> I am wondering how I put this in the prediction model.  First of all,
> I'm not sure whether I should be using a linrz_predict_model,
> linear_predict_model or Gaussian_predict_model. 

It's a non-linear system, so you have to use a linrz_predict_model (linearized 
prediction model).

> Second the matrix Fx 
> seems to implement x' = Fx(x) but I don't see how to incorporate the
> control component into the prediction.

For a linrz_predict_model (your case), you have to provide the prediction 
equations in the virtual function fx. Then Fx is the Jacobian matrix of 
partial derivatives relative to fx and must be updated at every time step 
using the previous state estimate and your control vector.
You will also need an observation model, linear or not, to correct the 
prediction according to the current observation.

Before, I suggest you to have a look at this nice introduction about Kalman 
filtering:
http://www.cs.unc.edu/~welch/kalman/kalmanIntro.html
Then you could have a look at the examples provided with Bayes++.

Hope it helps.

Nicola


-- 
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Nicola Bellotto
University of Essex
Department of Computer Science
Wivenhoe Park
Colchester CO4 3SQ
United Kingdom

Room: 1N1.2.8
Tel. +44 (0)1206 874094
URL: http://privatewww.essex.ac.uk/~nbello
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