diff --git a/tex/chapters/experiments.tex b/tex/chapters/experiments.tex
index 829acf0..6ba87a7 100644
--- a/tex/chapters/experiments.tex
+++ b/tex/chapters/experiments.tex
@@ -147,6 +147,8 @@
 
 	% error values
 	\begin{table}
+		\caption{Median error for walks conducted with the Nexus 6.}
+		\label{tbl:errNexus}
 		\centering
 		\begin{tabular}{|l|c|c|c|c|}
 			\hline
@@ -155,12 +157,12 @@
 			Shortest (\refeq{eq:transShortestPath})		&	\SI{2.72}{\meter}	&	\SI{2.98}{\meter}	&	\SI{2.48}{\meter}	&	\SI{3.06}{\meter}	\\\hline
 			Multipath (\refeq{eq:transMultiPath})		&	\SI{2.62}{\meter}	&	\SI{2.14}{\meter}	&	\SI{2.46}{\meter}	&	\SI{2.75}{\meter}	\\\hline
 		\end{tabular}
-		\caption{Median error for walks conducted with the Nexus 6.}
-		\label{tbl:errNexus}
 	\end{table}
 	
 	\begin{table}
-		\centering
+		\caption{Median error for walks conducted with the Galaxy S5.}
+		\label{tbl:errGalaxy}
+		\centering	
 		\begin{tabular}{|l|c|c|c|c|}
 			\hline
 														& Path1					& Path2					& Path3					& Path4 \\\hline
@@ -168,8 +170,6 @@
 			Shortest (\refeq{eq:transShortestPath})		&	\SI{ 5.86}{\meter}	&	\SI{4.14}{\meter}	&	\SI{5.14}{\meter}	&	\SI{5.20}{\meter}	\\\hline
 			Multipath (\refeq{eq:transMultiPath})		&	\SI{ 6.35}{\meter}	&	\SI{4.21}{\meter}	&	\SI{5.03}{\meter}	&	\SI{6.79}{\meter}	\\\hline
 		\end{tabular}
-		\caption{Median error for walks conducted with the Galaxy S5.}
-		\label{tbl:errGalaxy}
 	\end{table}
 	
 	%\begin{figure}
diff --git a/tex/chapters/grid.tex b/tex/chapters/grid.tex
index dcf7100..28c4fed 100644
--- a/tex/chapters/grid.tex
+++ b/tex/chapters/grid.tex
@@ -87,7 +87,7 @@
 		A* using the previously created graph would obviously lead to non-realistic paths sticking to walls and
 		walking many diagonals. Pedestrian's however, will probably keep a small gap between themselves and
 		nearby walls. To calculate paths that resemble this	behaviour, an importance-factor is derived for
-		each vertex. Those will be used to modify the euclidean distance $\fDistance{u}{v}$ between two vertices
+		each vertex. Those will be used to modify the distance $\fDistance{u}{v}$ between two vertices
 		$u,v$, examined by the shortest-path algorithm.
 		
 		To downvote vertices near walls, we need to determine the distance of each vertex from its nearest wall.
@@ -139,7 +139,7 @@
 		%
 		For $\mat{\Sigma}$, the two largest eigenvalues $\{\lambda_1, \lambda_2 \mid \lambda_1 > \lambda_2\}$
 		are calculated. If their ratio $^{\lambda_1}/_{\lambda_2}$ is above a certain
-		threshold, the neighbourhood describes a flat ellipse and thus either a door or a straight wall 
+		threshold, the neighbourhood describes a flat ellipse and thus either a door or a straight wall. 
 		%
 		To filter the latter, we enforce the euclidean distance \mbox{$\| \fPos{v} - \vec{c} \|$} between
 		the centroid and the vertex to be very small. Hereafter, only vertices located directly within a
@@ -251,7 +251,7 @@
 			%
 			As new states $\mStateVec_{t}$ should approach the pedestrian's destination
 			we use a reference $\pathRef$ all states try to reach. This references must
-			both, part of the shortest path and located somewhere outside of the sample-set.
+			be both, part of the shortest path and located somewhere outside of the sample-set.
 			%			
 			We thus calculate the standard deviation of the distance of all samples from the centre
 			$\pathCentroid$. After advancing the starting-vertex by three times this deviation
@@ -283,8 +283,8 @@
 		
 		\subsubsection{Multipath}
 		
-			The shortest-path algorithm mentioned in \ref{sec:pathEstimation} already calculated the
-			$\fLength{v}{\dot{v}}$ % = \sum_{i=s}^{e-1} \| v_{i} - v_{i+1} \| $
+			The shortest-path algorithm mentioned in \ref{sec:pathEstimation} already calculated the distance
+			$\fDistance{v}{\dot{v}}$ % = \sum_{i=s}^{e-1} \| v_{i} - v_{i+1} \| $
 			for the path from $v$ to the pedestrian's destination $\dot{v}$.
 			We thus apply the same assumption as \refeq{eq:transShortestPath} and downvote edges
 			not decreasing the distance to the destination:
@@ -296,7 +296,7 @@
 						\mathcal{N} (\angle e \mid \gHead, \sigma_\text{dev}^2) \cdot	\alpha \\
 						\alpha &= 
 						\begin{cases}
-							0.9 & \fLength{v'}{\dot{v}} < \fLength{v}{\dot{v}}		\\
+							0.9 & \fDistance{v'}{\dot{v}} < \fDistance{v}{\dot{v}}		\\
 							0.1 & \text{else}
 						\end{cases}
 				\end{split}