## 5 Discussion  
Table 1, obtained comparing different scans of the Leica Pegasus backpack, shows that RMS between the two georeferenced point clouds is 5.8 cm (absolute error case), whereas it reduces to 3.1 cm after registering them by using the ICP algorithm (relative error case). These results are actually in accordance with the Pegasus backpack specifications: 3 cm of relative accuracy indoors, whereas absolute position accuracy can go up to 50 cm for a ten-minute walk [15]. Despite that at first glance the numerical results reported above might suggest that the relative error of the proposed photogrammetric system can be potentially smaller than the Pegasus backpack's, actually this is apparently contradicted by examining the results obtained in Case (F) in Table 4. Case (F) is analogous to (A), but for the anchor positions, which were surveyed with Leica TCR 702 Total Station in this case. It is clear that Case (F) should be considered as an optimal anchor positioning case, i.e., UWB self-positioning is expected to lead to worse (or equal) performance. Consequently, the fact that RMS for Case (A) is lower than in Case (F) (and lower than the backpack's) should be  
Figure 10: **(a)** Map of point-to-point distances between TLS and photogrammetric point clouds in the WGS84 UTM32 coordinate system. UWB anchor positions surveyed with Leica TCR 702 Total Station. **(b)** Top view of the two georeferenced point clouds (TLS (blue) and the photogrammetric ones (gray)). Figure 9: **(a)** Map of point-to-point distances between TLS and photogrammetric point clouds in the WGS84 UTM32 coordinate system. **(b)** Top view of the two georeferenced point clouds (TLS (blue) and the photogrammetric ones (gray)). considered just a matter of chance. Instead, Case (F) shows that the expected \"best\" relative RMS error for photogrammetry with UWB self-positioning (9.7 cm) is worse than that of the Pegasus backpack (5.8 cm). Even though differences between the two Pegasus acquisitions are within the backpack's official margins of tolerance, Figure 3 shows that most significant differences are actually due to missing points in one of the two point clouds. Taking into account also laser scanning sensors' positions and orientations in the backpack (Figure 1b), this suggests that the completeness of the acquired dataset may depend also on the backpack's orientation with respect to the objects of interest during the survey: varying backpack orientation shall be a preferable working condition in order to ensure the acquisition of more complete datasets. Comparing backpack relative RMS errors, the negative influence of the final part of the bastion left wing is clear (Figure 4c): this area is intrinsically difficult to reconstruct, and both mobile mapping systems performed poorly in this part. This can be noted that even if actually this area has a more significant influence on the backpack error than on the photogrammetric one, which changes just from 6.1 cm to 4.6 cm by neglecting this area. Comparison of the Pegasus 3D model with the reference one (TLS, Section 2) confirms that Pegasus reconstruction is usually very accurate both in the relative (RMS = 4.6 cm, discarding the final part of the left wing) and in the absolute error case (RMS = 16.1 cm). Comparison of Cases (A) and (C) in Table 4 shows that UWB self-positioning in the low-cost photogrammetry presented in Section 4 allows obtaining a good scaling factor estimate and consequently reconstruction accuracy close to the optimal one (RMS = 6.1 cm and 5.9 cm, in the self-positioning and in the optimal scale case, respectively). This shows that if georeferencing is not needed, photogrammetric reconstruction with UWB self-positioning might be considered instead of the use of control points, in order to easily obtain a quite reliable metric reconstruction.