# A Visual Odometry Pipeline for Real-Time UAS Geopositioning
## 4 Experiments
### GIS Filtering and Its Effectiveness  
During the generation of the landmark dataset, detected landmarks in the geo-rectified orthophoto are kept or removed from the dataset depending on the type of object to which they belong. To facilitate this filtering, as discussed in [1], the geopositions of the landmarks are checked against the OpenStreetMap GIS information, and the landmarks that belong to buildings are removed. The resulting set of points generally lay on the roads and greenery. Noting that this filtering is offline, it does not increase the processing time of the platform geopositioning. The effect of GIS filtering on geopositioning can be analyzed in horizontal plane coordinates and platform attitude. The quantitative comparison for geopositioning accuracy with and without GIS filtering is shown in Tables 5 and 6, respectively, in horizontal and vertical directions. The table lists minimum, maximum, and mean (MAE) errors and the standard deviation of error. We can see from the results that pseudo-perspective and affine transformations provide better results than the homography transformation, especially when GIS filtering is enabled. We should note, however, that the horizontal accuracy does not change significantly with or without the GIS filter for the affine and pseudo-perspective transformations. \begin{table}
\begin{tabular}{c c c c c} \hline  & **Resi.** & **Campus** & **PKG.** & **Farm1** & **Farm2** \\ \hline Dis. (km) & 2.2 & 0.78 & 1.4 & 2.1 & 1.4 \\ Init. Orien. 1  & 180\({}^{\circ}\) & 0\({}^{\circ}\) & 60\({}^{\circ}\) & 90\({}^{\circ}\) & 180\({}^{\circ}\) \\ Init. Alt. (m) & 140 & 140 & 90 & 130 & 140 \\ Alt. Fluct.(m) 2  & 105–140 & 110–140 & 90–145 & 120–145 & 130–149 \\ \hline Min. Err. (m) 3  & 1.5 & 2.1 & 3.9 & 0.1 & 1.0 \\ Max. Err. (m) 3  & 10.1 & 9.6 & 9.7 & 7.4 & 5.1 \\ MAE (m) 3  & 6.0 & 6.3 & 7.1 & 4.0 & 3.4 \\ Std (m) 4  & 1.74 & 1.74 & 1.07 & 1.54 & 1.07 \\ \hline Min. Err. (m) 5  & 0.0 & 0.0 & 2.0 & 0.0 & 0.0 \\ Max. Err. (m) 5  & 12.3 & 6.4 & 6.1 & 5.30 & 4.1 \\ MAE (m) 5  & 2.9 & 1.8 & 4.5 & 1.8 & 1.2 \\ Std (m) 6  & 3.1 & 1.53 & 0.70 & 1.25 & 1.05 \\ \hline \end{tabular}
\end{table} 
Table 4: The flight-plan information (first quad) and the predicted horizontal (second quad) and vertical (third quad) geopositioning quantitative analysis against reference geospatial data. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**GIS Filter**} & \multirow{2}{*}{**Transformation**} & \multicolumn{4}{c}{**Residential Area**} & \multicolumn{4}{c}{**University Campus**} & \multicolumn{4}{c}{**Parking**} & \multicolumn{4}{c}{**Farm1**} \\ \cline{3-14}  & & **Min.** & **Max.** & **MAE** & **Std.** & **Min.** & **Max.** & **MAE** & **Std.** & **Min.** & **Max.** & **MAE** & **Std.** \\ \hline \multirow{3}{*}{Activated} & Pseudo-perspective & 1.5 & **10.1** & **6.0** & 1.74 & 2.1 & **9.6** & 6.3 & 1.74 & 3.9 & 9.7 & **7.1** & 1.07 & **0.1** & **7.4** & **4.0** & **1.54** \\  & Affine & 1.6 & 10.4 & **6.0** & **1.69** & 2.4 & 9.7 & 6.3 & 1.71 & 3.9 & **9.5** & **7.1** & **1.06** & **0.1** & 7.6 & 4.1 & 1.55 \\ \cline{1-1}  & Homography & 0.9 & 16.0 & 7.3 & 2.68 & 1.6 & 18.5 & 7.6 & 3.15 & 4.4 & 16.0 & 8.0 & 1.74 & 0.3 & 11.1 & 5.0 & 2.26 \\ \hline \multirow{3}{*}{Deactivated} & Pseudo-perspective & 1.5 & **10.1** & **6.0** & 1.71 & 1.9 & 9.8 & **5.7** & 1.61 & 3.9 & 9.7 & **7.1** & 1.08 & **0.1** & 7.7 & **4.0** & **1.54** \\ \cline{1-1}  & Affine & 1.7 & 10.3 & **6.0** & 1.70 & 2.4 & 9.8 & **5.7** & **1.57** & 3.7 & **9.5** & **7.1** & 1.08 & **0.1** & 7.8 & 4.1 & **1.54** \\ \cline{1-1}  & Homography & **0.8** & 15.7 & 7.4 & 2.80 & **1.0** & 26.9 & 8.6 & 4.60 & **3.2** & 27.1 & 8.3 & 2.40 & 0.3 & 33.7 & 5.1 & 2.96 \\ \hline \end{tabular}
\end{table} 
Table 5: Horizontal UAS geopositioning accuracy tabulated by minimum, maximum, mean absolute error, and standard deviation (in meters) under three transformation variants and activating or deactivating the GIS filter.