wrote short paragraph about measurements close to sensor

thesis/Main.tex

@@ -292,6 +292,22 @@
       \caption{Density histogram showing the percentage of missing measurements per scan for normal experiments without degradation and anomalous experiments with artifical smoke introduced as degradation.}\label{fig:data_missing_points}
     \end{figure}
     %END missing points
+
+    %BEGIN early returns
+
+    % In experiments with artifical smoke present, we observe many points in the pointcloud very close to the sensor where there are no solid objects and therefore the points have to be produced by airborne particles from the artifical smoke. The phenomenon can be explained, in that the closer to the sensor an airborne particle is hit, the higher the chance of it reflecting the ray in a way the lidar can measure. In \ref{fig:particles_near_sensor} we see a box diagram depicting how significantly more measurements of the anomaly expirements produce a range smaller than 50 centimeters. Due to the sensor platform's setup and its paths taken during experiments we can conclude that any measurement with a range smaller than 50 centimeters has to be erroneous. While the amount of these returns near the sensor could most likely be used to estimate the sensor data quality while the sensor itself is located inside an environment containing airborne particles, this method would not allow to anticipate sensor data degradation before the sensor itself enters the affected area. Since lidar is used to sense the visible geometry from a distance, it would be desireable to quantify the data degradation of an area before the sensor itself enters it. Due to these reasons we did not use this phenomenon in our work.
+
+    In experiments with artificial smoke, we observe numerous points in the point cloud very close to the sensor, even though no solid objects exist at that range. These points are therefore generated by airborne particles in the artificial smoke. This phenomenon occurs because the closer an airborne particle is to the sensor, the higher the probability it reflects the laser beam in a measurable way. As shown in Figure~\ref{fig:particles_near_sensor}, a box diagram illustrates that significantly more measurements during these experiments report ranges shorter than 50 centimeters. Given the sensor platform's setup and its experimental trajectory, we conclude that any measurement with a range under 50 centimeters is erroneous.
+
+While the density of these near-sensor returns might be used to estimate data quality when the sensor is already in an environment with airborne particles, this method cannot anticipate data degradation before the sensor enters such an area. Since LiDAR is intended to capture visible geometry from a distance, it is preferable to quantify potential degradation of an area in advance. For these reasons, we did not incorporate this phenomenon into our subsequent analysis.
+
+    \begin{figure}
+      \begin{center}
+        \includegraphics[width=0.9\textwidth]{figures/particles_near_sensor_boxplot_zoomed_500.png}
+      \end{center}
+      \caption{Box diagram depicting the percentage of measurements closer than 50 centimeters to the sensor for normal and anomalous experiments}\label{fig:particles_near_sensor}
+    \end{figure}
+    %END early returns
     
     \todo[inline]{describe data sources, limitations}
     \todo[inline]{screenshots of camera/3d data?}