Commit a174c57b authored by Martina Maggio's avatar Martina Maggio
Browse files

starting to address reviewers comments

parent ff52f485
......@@ -29,7 +29,7 @@ font=\footnotesize]
\draw [arr, bend left] (gp) to node [near start, left, yshift=4mm, align=right] {\texttt{sensor in}\\\texttt{position\_available} \\ \textcolor{red}{\texttt{turn\_off}}} (wst);
\draw [arr, bend right] (gp) to node [below, align=center, yshift=-1mm] {\texttt{lost\_visibility} \textbf{\texttt{or}} \\ \texttt{ephemeris\_expiring}} (re);
%arrows from 4
\draw [arr, bend left] (wst) to node [right, align=left, xshift=2mm, yshift=-3mm, at start] {\texttt{$\sum(\Tr(P)>th)$} \\ \texttt{\textcolor{red}{\texttt{turn\_on}}}} (gp);
\draw [arr, bend left] (wst) to node [right, align=left, xshift=2mm, yshift=-3mm, at start] {\texttt{$\Tr(P)>th$} \\ \texttt{\textcolor{red}{\texttt{turn\_on}}}} (gp);
\draw [arr, bend right] (wst) to node [left, at start, yshift=4mm, align=right] {\texttt{ephemeris\_expiring} \\ \textcolor{red}{\texttt{turn\_on}}} (re);
\end{tikzpicture}
\caption{State Machine of the Sampling Strategy Controller.}
......@@ -61,7 +61,7 @@ milliseconds to be acquired. This could be critical for real-time
applications. The data validity is instantaneous, since they are used
as soon as they are received to compute the current position (and
moving will invalidate them). The time scale allows us to derive a
bound in the sensor sampling period. Sampling as frequently as the
bound in the sensor sampling period. Sampling as frequently as
this (lower) bound is equivalent to keeping the sensor always on.
Another important consequence of the sampling policy is the
......
......@@ -296,7 +296,7 @@ synchronized in the antenna's state.
legend style={at={(1.3,1.1)},anchor=south},
legend columns=2,
xlabel = {Time [s]},
ylabel = {Sum of Trace \\ Turn On Signal},
ylabel = {Trace \\ Turn On Signal},
xmin=500,xmax=3500,
]
\pgfplotsset{filter discard warning=false}
......@@ -312,11 +312,11 @@ synchronized in the antenna's state.
\addplot[thick, red, dashed]
table[x index = {0}, y index = {2}, col sep=comma]
{data/exp_biketraceCtl.csv};
\addlegendentry{Sensor Fusion $th = 0.1$, $\sum Tr(P)$}
\addlegendentry{Sensor Fusion $th = 0.1$, $Tr(P)$}
\addplot[thick, black!70!green, dashed]
table[x index = {0}, y index = {4}, col sep=comma]
{data/exp_biketraceCtl.csv};
\addlegendentry{Sensor Fusion $th = 4.1$, $\sum Tr(P)$}
\addlegendentry{Sensor Fusion $th = 4.1$, $Tr(P)$}
\end{axis}
\end{tikzpicture}
\caption{Control Signal and Sampling when cycling.}
......@@ -335,7 +335,7 @@ synchronized in the antenna's state.
scaled y ticks = false,
ylabel style = {align=center},
xlabel = {Time [s]},
ylabel = {Sum of Trace \\ Turn On Signal},
ylabel = {Trace \\ Turn On Signal},
xmin=500,xmax=3500,
]
\pgfplotsset{filter discard warning=false}
......@@ -389,7 +389,7 @@ algorithm is very basic and more advanced versions could improve the
tracking performance also in the biking case. For the same
simulations, we also show in Figures~\ref{fig:bike-trace-ctl}
and~\ref{fig:car-trace-ctl} the signal used for the GPS triggering
(i.e., the sum of the trace of $P$) and the state of the GPS antenna.
(i.e., the trace of $P$) and the state of the GPS antenna.
The figures show how the sampling strategy is able to keep the
variance of the estimation bounded, while reducing the on time.
......
Supports Markdown
0% or .
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment