## 4 Experimental Results
### Experimental Validation
\begin{table}
\begin{tabular}{c c c c c c c c c c c c} \hline \hline  & \multicolumn{3}{c}{**Map 1**} & \multicolumn{3}{c}{**Map 2**} & \multicolumn{3}{c}{**Map 3**} & \multicolumn{3}{c}{**Map 4**} & \multicolumn{3}{c}{**Map 5**} & \multicolumn{3}{c}{**Map 6**} \\ \cline{2-13}  & **m** & \({}^{\circ}\) & **m** & \({}^{\circ}\) & **m** & \({}^{\circ}\) & **m** & \({}^{\circ}\) & **m** & \({}^{\circ}\) & **m** & \({}^{\circ}\) \\ \hline Carto25 m local/unoptimized & 8.9 & 10.3 & 9.7 & 9.5 & 11.1 & 9.9 & 9.7 & 17.5 & 34.3 & 7.7 & 110 & 35.9 \\ Carto60 m local/unoptimized & 2.0 & 1.4 & 0.4 & 1.3 & 7.6 & 2.6 & 0.5 & 15 & 13.9 & 5.1 & 35 & 9.5 \\ AMDS (60 m/25 m) & 2.1 & 1.4 & 0.4 & 1.3 & 7.6 & 2.6 & 0.6 & 1.5 & 15.9 & 5.0 & 37 & 9.6 \\ Local/unoptimized & & & & & & & & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Measured drift error translation (m) and rotation (\({}^{\circ}\)). Figure 11: Map accuracy and detail: (**a**) Result map 1, (**b**) result map 4, (**c**) result map 6, (**1**) Cartographer using 25 m scan distances, and (**2**) Cartographer using adaptive multistage distance scheduler (AMDS) (60 m/25 m) scan distances. The analysis of the map generated from AMDS provides detailed information of AMDS accuracy. The overall result of the Cartographer map generation from the experiment highlights the important areas only. The information is shown in Figure 11.  
From the map generation, as shown in Figure 11.a, it can be observed that the AMDS (60 m/25 m) still preserves map detail and better accuracy than the 25 m scan. A smaller scan cannot sample feature that is out of scan range. Figure 11a.2 shows the area where structures are missing. In AMDS, the missing gap of a smaller scan are filled by larger scans with the help of scheduler. Thus, the missing building still can be reconstructed inside the map. A smaller scan also has an increased error penalty when the road has an extreme downward and upward slope. The scan matcher judgment of Cartographer performs poorly as it does not have enough feature information to increase pose confidence when aligning the scan in a 2D map. Performance of the AMDS (60 m/25 m) has better results in this area, as shown in Figure 11b.2. In addition, map with upward downward roads and vegetation also contributes to the increased error of Cartographer. In long distance travel, the 25 m scan performs even more poorly. Similar bad drift results also apply to NDT-SLAM that does not use global optimization in vegetation areas. Map 6 highlights a 2 km total distance traveled and the result for the 25 m scan Cartographer drift of approximately 110 m from the starting position point. The result is visible in Figure 11c.1, whereas Figure 11c.2 shows reduced drift errors. It is no0 ted that the LOAM has a massive performance drop in map 6, as shown in Table 4 and Figure 10f. The LOAM started to drift heavily at areas around road intersections and these areas have large empty open spaces. This kind of area is not suitable for LOAM to extract specific feature information such as edge lines and planar surfaces and eliminates other information. To show the comparison of complete pose generation time of AMDS, NDT, LOAM, we tested Cartographer in various urban road environments. The average results are shown in Figure 12. The proposed AMDS in Cartographer boosts speed up to 16% faster than the standard 60 m scan Cartographer. The processing speed also varies based on travel distance. AMDS with 0.5 km travel distances generates pose faster, at approximately 21 ms. This increases linearly as the maps become larger. As shown in Figure 12, 1 km, 1.5 km, and 2 km travel distances generate poses at approximately 23 ms, 27 ms, and 34 ms respectively. The AMDS Cartographer technique also has several advantages as compared with other SLAM methods such as NDT and LOAM. On the one hand, in terms of speed performance, it is several times faster than NDT-SLAM as it can generate map data online. Map generation in the NDT-SLAM, on the other hand, needs to be processed offline before it can be plotted.