# A Comparative Study of Indoor Accuracies Between SLAM and Static Scanners
## 3 Results
### Comparison of Scanners from the Perspective of Noise  
Table 5 shows the mean RMSE before smoothing, after smoothing, and noise levels for all scanners (means of all profiles and, in the case of SLAM scanners, also of all measurements). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Scanner** & \begin{tabular}{c} **RMSE\({}_{\text{2X}}\)** \\ **(StDev) [mm]** \\ \end{tabular} & \begin{tabular}{c} **RMSE\({}_{\text{2X}}\)** \\ **(StDev) [mm]** \\ \end{tabular} & \begin{tabular}{c} **RMSE\({}_{\text{2Z}}\)** \\ **(StDev) [mm]** \\ \end{tabular} & \
\begin{tabular}{c} **RMSE\({}_{\text{MIN/MAX}}\)** \\ **(StDev) [mm]** \\ \end{tabular} &
\begin{tabular}{c} **RMSE\({}_{\text{1 CPC-profile}}\)** \\ **(StDev) [mm]** \\ \end{tabular} \\ \hline Trimble X7 & 8.8 (1.8) & 0.6 (0.5) & 1.2 (0.5) & 10.0 (X) & 1.2 (0.2) \\ Leica RTC 360 & 0.9 (0.5) & 0.2 (0.3) & 0.5 (0.6) & 1.2 (X) & 0.6 (0.1) \\ Emesent & 9.8 (5.6) & 2.2 (2.2) & 2.3 (2.3) & \(-\)18.2 (X) & 5.5 (0.6) \\ GeoSLAM ZEB & & & & & \\ Horizon RT & 71.1 (14.4) & 10.7 (7.8) & 4.2 (4.4) & \(-\)96.4 (X) & 12.1 (0.7) \\ FARO Orbis & 11.2 (5.7) & 2.9 (2.7) & 6.4 (2.9) & \(-\)18.0 (X) & 5.2 (0.2) \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Local accuracies (based on three profiles in the cloud) acquired as mean displacements from the ICP transformation matrix and standard deviation (StDev in the brackets). \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Scanner** & \begin{tabular}{c} **RMSE\({}_{\text{ICP-local}}\) (StDev)** \\ **[mm]** \\ \end{tabular} & \
\begin{tabular}{c} **RMSE\({}_{\text{ICP-local smoothed}}\)** \\ **[mm]** \\ \end{tabular} &
\begin{tabular}{c} **RMSE\({}_{\text{noise}}\) (StDev) [mm]** \\ \end{tabular} \\ \hline Trimble X7 & 1.2 (0.2) & 0.9 (0.1) & 0.9 (0.2) \\ Leica RTC 360 & 0.6 (0.1) & 0.7 (0.1) & - \\ Emesent & 5.5 (0.6) & 2.2 (0.5) & 5.0 (0.5) \\ Hovermap ST-X & & & & \\ GeoSLAM ZEB & & & & \\ Horizon RT & 12.1 (0.7) & 7.6 (1.1) & 9.3 (0.3) \\ FARO Orbis & 5.2 (0.2) & 2.1 (0.4) & 4.7 (0.2) \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Mean RMSE values and standard deviation (StDev in the brackets) before smoothing, after smoothing, and noise for individual scanners. The results clearly show that static scanners suffer from only a minimum noise. In the case of Leica RTC 360, smoothing even worsened the results, which prevented the noise calculation. On the other hand, GeoSLAM ZEB Horizon RT with its noise value of >9 mm performed the worst. SLAM scanners generally suffered from greater noise than static ones; after smoothing, however, the accuracies of the new-generation SLAM scanners were not far from that of static scanners. The technological advancement in the newer generations of SLAM scanners is obvious. Figure 15 shows the effect of smoothing on GeoSLAM ZEB Horizon RT (Figure 15a--raw data, Figure 15b--after smoothing). The figure clearly demonstrates the benefit of smoothing on the noise reduction while, on the other hand, deteriorating the quality of sharp corners detection. Visual Comparison  
To better illustrate the numerical values, visual comparisons were added. The figures depict the clouds (a) before and (b) after smoothing. Note that color scales vary among scanners to reflect differing maximum RMSE values. The RMSE values shown in the figures are always valid for the particular depicted situation--the central profile in the static scanners and the central profile of the second measurement in SLAM scanners. In static scanners, smoothing led to a minor improvement in accuracy, which was, however, at the cost of minor edge rounding and, therefore, a slight deterioration of the representativeness of the data. This is less pronounced in Trimble X7 (Figure 16) than in Leica RTC 360 (Figure 17). In SLAM scanners, the improvement brought about by smoothing was greater than in static scanners, which was most noticeable in the vertical component. While Emesent Hovermap ST-X (Figure 18) and FARO Orbis (Figure 19) showed maximum errors of approx.