+As presumed in Section \ref{exp1:results}, errors in the Roomba's movements
+could originate from imprecise measurement of the Roomba's internal sensors or
+in the Wiselib implementation. So a natural approach to correct this sort of
+errors would be to average the results for each data point from Experiment 1,
+find a function that fits the mean measured error depending of the
+target velocity and target distance or angle as well as possible, and then
+adapting either one of the target parameters so that the resulting movement
+would most likely be the desired target value. In this experiment however, only
+the target distance resp. the target angle was adjusted, while the velocity
+remained unadjusted.
+
+Fitting the function\index{fit function} was done with \acs{GNU} R\index{GNU R}
+through the wrapper script \prog{graph.sh} which is explained in
+section~\ref{sec:impl:eval}. In this experiment, a 2-dimensional linear fit for
+the measured value was determined by the method of least squares, with target
+value (angle or distance) and velocity as input parameters. The fit function was
+then used in the algorithm to calculate the adapted target distance or angle.