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Fixed top margin of algo float

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Markus Bullmann
2018-05-09 12:29:40 +02:00
parent 7590b9642c
commit a7be6b8d62
2 changed files with 21 additions and 3 deletions
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tex/chapters/realworld.tex
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@@ -7,10 +7,10 @@ At a given time $t$ the system estimates a state providing the most probable pos
It is implemented using a particle filter with sample importance resampling and \SI{5000} particles.
The dynamics are modelled realistically, which constrains the movement according to walls, doors and stairs.
We arranged a \SI{223}{\meter} long walk within the first floor of a \mbox{\SI{76}{} $\times$ \SI{71}{\meter}} sized museum, which was built in the 13th century and therefore offers non-optimal conditions for localization.
We arranged a \SI{223}{\meter} long walk within the first floor of a \mbox{\SI{76}{} $\times$ \SI{71}{\meter}} sized museum, which was built in the 13th century and offers non-optimal conditions for localization.
%The measurements for the walks were recorded using a Motorola Nexus 6 at 2.4 GHz band only.
%
Since this work only focuses on processing a given sample set, further details of the localisation system and the described scenario can be looked up in \cite{Ebner17} and \cite{Fetzer17}.
Since this work only focuses on processing a given sample set, further details of the localization system and the described scenario can be looked up in \cite{Ebner17} and \cite{Fetzer17}.
The spacing $\delta$ of the grid was set to \SI{27}{\centimeter} for $x$ and $y$-direction, resulting in a grid size of $G=74019$.
The bivariate state estimation was calculated whenever a step was recognized, about every \SI{500}{\milli \second}.
%The intention of a real world experiment is to investigate the advantages and disadvantages of the here proposed method for finding a best estimate of the pedestrian's position in the wild, compared to conventional used methods like the weighted-average or choosing the maximum weighted particle.