On Tue, Aug 12, 2014 at 12:00 PM, <bfl-request [..] ...>
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> Today's Topics:
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> 1. Bind variables in BFL filter (Ugo Cupcic)
>
>
> ---------- Forwarded message ----------
> From: Ugo Cupcic <ugo [..] ...>
> To: <bfl [..] ...>
> Cc:
> Date: Mon, 11 Aug 2014 15:45:57 +0200
> Subject: [BFL] Bind variables in BFL filter
> Hi,
>
> We're trying to use a Bayesian Filter to do some sensor fusion for
> estimating the joints positions on a joint based robot (estimated with
> different sensors).
>
> We now have two versions of the same filter (one using
> ExtendedKalmanFilter, the other one a particle filter: BootstrapFilter)
> that converges but haven't yet found a way of binding the BFL state
> representation variables. In our case, we'd like to make sure that each
> variable of the state stays within the joint limits.
>
> Feel free to ask for more details as I'm not exactly sure what is most
> relevant.
>
>
Hi Ugo,
I am no expert, but I'll give you my opinion anyway.
I might be wrong, but is it possible that by "binding" you actually mean
"constraining"?
If that is the case, than I am afraid there is no "clean" way of doing this.
If the state variables are defined by Gaussian pdfs, than by definition
those span an infinite support.
You could try to make variables outside of the joint limits "highly
unlikely" by filtering your measurements, and rejecting those outside a
validation area, or carefully defining Process noise and Measurement Noise
Covariance Matrices, but if you really want to use constraints, that
you're actually solving an Estimation + Constrained Optimization problem,
and you'll need different tools for that.
Cheers,
Enrico
Cheers,
>
> Ugo
>
> PS: sorry for cross-posting on ROS-answers
> http://answers.ros.org/question/189700/bfl-bind-variables/
> --
> Ugo Cupcic *Senior Software Engineer*+44 20 7700 2487ugo [..] ...
> www.shadowrobot.com
>
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