# A Comparative Study of Indoor Accuracies Between SLAM and Static Scanners
## 4 Discussion  
Over the last years, SLAM scanners and their performance have become a focus of the expert community. SLAM technology was investigated, for example, in [28], where the quality of the resulting point clouds acquired using different SLAM algorithms was studied. The authors achieved accuracies of several centimeters to decimeters; however, the reported accuracies were only calculated based on manual measurement of several points in the study area, lacking the robustness required for a comprehensive statistical evaluation. [PERSON] et al. [29] compared multiple algorithms for processing of SLAM data acquired using a SLAM scanner mounted on a robotic vehicle and compared the results with the reference cloud acquired using a terrestrial scanner. They achieved point cloud accuracies (RMSEs compared to the reference cloud) of approx. 0.05 m, increasing up to 0.1 m in a narrow walkway. In [30], the GeoSLAM scanner was evaluated in underground environments, yielding RMSEs of 5-6 cm. The authors, however, did not compare the results to reference data--the comparison was limited to evaluation of the differences between two passes using the same scanner. In another study [31], Emesent Hovermap ST was tested in a similar environment, reporting accuracy of about 15 mm over approx. 45 m. It, however, needs to be mentioned that this value is not the absolute error but the error after ICP transformation (without any transformation to spherical points). When the same test was performed in a 150 m long corridor, however, Mean Absolute Deviation (MAD; relative to a reference cloud) increased to 0.1 m despite the ICP transformation (compare to 5.8 mm in our study at 80 m). In another study [32], the Emesent Hovermap ST-X (the same version as in our paper; newer than in [31]) yielded a transverse accuracy of \(\sim\)0.4 m at 750 m (one-way scan), improving to 0.1 m when a closed loop (i.e., round trip) was used for data acquisition. In [33], three SLAM scanners were tested in underground spaces (approx. 75 m long) with walls made of shaped stones and bricks and compared with a terrestrial static scanner. GeoSLAM yielded an RMSE of 0.017 m; it, however, needs to be said that in that study,  
Figure 20: Profile 2 acquired by GeoSLAM ZEB Horizon RT (**a**) before (RMSEICP-Local = 11.9 mm); and (**b**) after smoothing (RMSEICP-Local smoothed = 7.4 mm). the transformation to reference data was always performed locally, no global result for the entire length of the space was reported. A more comprehensive study [34] comparing the performance of multiple static and SLAM scanners in underground spaces to the reference data (Leica P40) reported RMSEs of SLAM scanners to be in the order of centimeters, which corresponds with the results of the current study. Another paper described the use of a SLAM scanner GeoSLAM REVO for scanning a castle and adjacent space [35], also reporting the errors of a few centimeters. Similar accuracies have been also reported in [36], where GeoSLAM ZEB Horizon RT was used for capturing a concrete bridge construction. The accuracy of SLAM scanners in the interior of buildings was also discussed in [37], where it was combined with terrestrial scanning. Again, the accuracies were better than 0.05 m; it was, however, determined only using spatial distances between spherical targets placed in the individual rooms of the mapped indoor space. Results of the tests performed in our study show that static scanners still remain the best choice for indoor measurements if accuracy is of paramount importance. The technological progress of SLAM scanners is, however, significant and with appropriate post-processing (e.g., ICP alignment and smoothing), these devices can deliver point cloud accuracies that are sufficient for most common surveying applications. Besides the speed of scanning, the fact that with SLAM scanners, occlusions are practically eliminated, represents an additional advantage of SLAM scanners.