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final version of paper

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toni
2016-06-02 15:57:53 +02:00
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tex/chapters/introduction.tex
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@@ -75,7 +75,7 @@ As one can imagine, this can lead to serious problems in big indoor environments
Such a situation can be improved by incorporating future measurements (e.g. the right turn)
%or predictive information (e.g. the most likely path)
to the filtering procedure \cite{Ebner-16}.
However, standard filtering methods are not able to use any future information and the possibilities to make a distant forecast are also limited \cite{robotics, Doucet11:ATO, chen2003bayesian}.
However, standard filtering methods are not able to use any future information and the possibilities to make a distant forecast are also limited \cite{Doucet11:ATO, chen2003bayesian, doucet2000}.
One promising way to deal with these problems is smoothing.
Smoothing methods are able to make use of future measurements for computing their estimation.