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

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

Have been fiddeling arround for an hour. Could it be that I need to
replace the linear prediction model with an "Unscented_predict_model"?
I would derive from the mentioned model and then overwrite the
function "f" to insert my own state transition function? Same with the
noise i.e. covariance matrix Q?

Vinh

On 11/13/06, Vinh <arb...@go...> wrote:
> 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
>