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minor tex changes

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FrankE
2016-02-29 13:31:55 +01:00
parent 44120a63a5
commit 59fbcd1b1b
1 changed files with 16 additions and 12 deletions
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tex/chapters/experiments.tex
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@@ -6,7 +6,7 @@
Evaluation took place within all floors (0 to 3) of the
faculty building, each of which about \SI{77}{\meter} x \SI{55}{\meter} in size.
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We conducted 4 distinct walks, to test short distances, long distances, critical sections
We conducted 4 distinct walks, to test short and long distances, critical sections
and ignoring the shortest-path suggested by the system.
Due to an in-house exhibition during that time, many places were crowded and \docWIFI{} signals
are attenuated.
@@ -15,15 +15,19 @@
While walking, the pedestrian clicked a button on the smartphone application
when passing a marker. Between two consecutive points, a constant movement speed is assumed.
Thus, the ground truth might not be \SI{100}{\percent} accurate, but fair enough for error measurements.
All walks were performed using a Motorola Nexus 6 and a Samsung Galaxy S5.
As the Samsung Galaxy S5's \docWIFI{} can not be limited to the \SI{2.4}{\giga\hertz} band only,
its scans take much longer than those of the Motorola Nexus 6:
All walks were performed using a Motorola Nexus 6 and a Samsung Galaxy S5.
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As the Galaxy's \docWIFI{} can not be limited to the \SI{2.4}{\giga\hertz} band only,
its scans take much longer than those of the Nexus:
\SI{3500}{\milli\second} vs. \SI{600}{\milli\second}.
Also, the Nexus' barometer sensor provides readings both more frequent and far more accurate than
the Galaxy does. This results in a better localisation using the Nexus smartphone.
Despite being fast enough to run in realtime on the smartphone itself, computation was done offline using
the \mbox{CONDENSATION} particle filter with \SI{7500}{} particles as realization.
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Despite being fast enough to run on the smartphone itself
($ \approx \SI{100}{\milli\second} $ per transition, single-core Intel\textsuperscript{\textregistered} Atom{\texttrademark} C2750),
computation was done offline using
the \mbox{CONDENSATION} algorithm with \SI{7500}{} particles as realization.
The weighted arithmetic mean of the particles was used as state estimation.
As mentioned earlier, the position of all \docAP{}s (about 5 per floor) is known beforehand.
@@ -104,15 +108,15 @@ All walks were performed using a Motorola Nexus 6 and a Samsung Galaxy S5.
segment \refSeg{1} of fig. \ref{fig:errorTimedNexus}.
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Starting instead with both, known position and heading, reduced the error by about \SI{15}{\percent} when using prior knowledge and
by \SI{25}{\percent} when omitting prior knowledge. As prior knowledge directs the density towards a known target,
it is able to compensate unknown initial headings which explains the \SI{10}{\percent} difference.
by \SI{25}{\percent} when omitting prior knowledge. As prior knowledge directs the density towards the known target,
it is able to compensate initially unknown headings which explains the \SI{10}{\percent} difference.
%
However, as soon as the pedestrian starts moving down the hallway \refSeg{2} the error is reduced dramatically.
As soon as the pedestrian starts moving down the hallway \refSeg{2} the error is reduced dramatically.
Adding prior knowledge centres the density in the middle of the floor, ensures that the heading is directed towards
the shortest path and thus produces even better localisation results.
%
Directly hereafter, we ignore the shortest path \refSeg{3'} determined by the system and walk along \refSeg{3}
instead. Of course, this leads to a temporally increasing error, as the system needs to detect this path change
instead. Of course, this leads to a temporarily increasing error, as the system needs to detect this path change
and takes some time to recover (see fig. \ref{fig:errorTimedNexus} \refSeg{3}). The new path to the desired destination
is \refSeg{3''} which is also ignored. Instead, we took a much longer route down the stairwell \refSeg{4}.
After this change is detected by the system, prior knowledge is again able to reduce the error for segment \refSeg{5}.
@@ -130,9 +134,9 @@ as seen in fig. \ref{fig:nexusPathDetails} \refSeg{6}.
errors in segment \refSeg{7}.
It follows a critical area with high errors and multimodalities.
Due to an in-house exhibition during the time of recording, we had to leave the ground truth by a few meters.
Furthermore, the overcrowded areas lead to attenuated \docWIFI{} signals. Both reasons move the
Furthermore, the overcrowded areas lead to attenuated \docWIFI{} signals. This moves the
density into another stairwell (see fig. \ref{fig:nexusPathDetails}, red lines in the lower right).
The resulting multimodality (two staircases possible) leads to a rising error
The resulting multimodality (two staircases possible) leads to a rising error in
\refSeg{8}, \refSeg{9}. At the end of the walk \refSeg{10} the system is able to recover, again.