some minor gfx changes
some minor tex changes
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@@ -1,5 +1,7 @@
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\section{Experiments}
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\newcommand{\refSeg}[1]{seg. $#1$}
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% introduction
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Evaluation took place within all floors (0 to 3) of the
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faculty building, each of which about \SI{77}{\meter} x \SI{55}{\meter} in size.
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@@ -49,6 +51,8 @@
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are omitted from the error calculation to allow the system to somewhat settle its initial state. Even though, the error
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during the following few seconds is expected to be much higher than the error when starting with a well known initial
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position and heading.
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%
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The following evaluations will depict the improvements that the prior path knowledge is able to provide,
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even when other system parameters are badly chosen.
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@@ -73,10 +77,10 @@
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% error development over time while walking along a path
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\begin{figure}
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\input{gfx/eval/error_timed_nexus}
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\caption{Development of the error while walking along Path 4 using the Motorola Nexus 6.
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When leaving the suggested route (3), the error of \textbf{shortest} path \refeq{eq:transShortestPath}
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\caption{Error development while walking along Path 4 using the Motorola Nexus 6.
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When leaving the suggested route \refSeg{3}, the error of \textbf{shortest} path \refeq{eq:transShortestPath}
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and \textbf{multi}path \refeq{eq:transMultiPath} increases.
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The same issues arise when facing multimodalities between two staircases just before the destination (9).
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The same issues arise when facing multimodalities between two staircases just before the destination \refSeg{9}.
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\commentByFrank{hilft das bold vlt. schon um die legende zu verstehen?}
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}
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\label{fig:errorTimedNexus}
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@@ -85,13 +89,14 @@
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\begin{figure}
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\input{gfx/eval/path_nexus_detail}
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\caption{Detailed path analysis depicting the individual segments of path 4 using \refeq{eq:transMultiPath}.
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Their corresponding error can be seen in fig. \ref{fig:errorTimedNexus}. Even though the shortest path
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suggested by the system is ignored multiple times ($3'$ and $3''$) our approach is still able to improve
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For a better visualisation, the segments are divided using an outline of alternating grey levels.
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The corresponding segment-error can be seen in fig. \ref{fig:errorTimedNexus}. Even though the shortest path
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suggested by the system is ignored multiple times (\refSeg{3'} and \refSeg{3''}) our approach is still able to improve
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the overall localisation error.}
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\label{fig:nexusPathDetails}
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\end{figure}
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%
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\newcommand{\refSeg}[1]{$(#1)$}
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Fig. \ref{fig:errorTimedNexus} depicts the error for path 4 recorded with the Motorola Nexus 6.
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For a better understanding of the following discussion, the path was divided into $10$ individual segments.
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@@ -106,6 +111,11 @@
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This can be seen at the red area in the upper left corner of fig. \ref{fig:nexusPathDetails} \refSeg{1} and within
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segment \refSeg{1} of fig. \ref{fig:errorTimedNexus}.
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%
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Starting with both, known position and heading, reduced the error by about \SI{15}{\percent} when using prior knowledge and
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by \SI{25}{\percent} when omitting prior knowledge. As prior knowledge directs the density towards a known target,
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it is able to compensate unknown initial headings which explains the \SI{10}{\percent} difference.
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\commentByFrank{bekannter startpunkt getestet und kurz beschrieben}
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%
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However, as soon as the pedestrian starts moving down the hallway \refSeg{2} the error is reduced dramatically.
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Adding prior knowledge centres the density in the middle of the floor, ensures that the heading is directed towards
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the shortest path and thus produces even better localisation results.
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