## 2 State-of-the-Art of Systems for Indoor Mobile Mapping (iMMS)
In order to reduce the effects of such geometric drift, numerous SLAM-based tools are forced to ensure that the starting point of the mapping procedure coincides with the endpoint of the survey [51]. Nonetheless, these technologies have the significant advantage of facilitating the rapid survey of large sites, producing survey accuracies frequently aligned with the requirements of a real estate rehabilitation project, typically within 1-2 cm locally and several centimeters in the global model. SLAM technology greatly simplifies field measuring processes while simultaneously reducing their costs. Since centimeter-level accuracy is not required for the global model in geospatial projects, the setup of control points or control scans can be abandoned in such applications [52; 53]. An important advantage of SLAM-based iMMS techniques is the ability to operate in hybrid environments, which include both outdoor and indoor conditions, with the primary constraint being the need for adequate three-dimensional geometry in the surveyed areas [54; 55]. This limitation precludes open areas lacking geometrical features, such as broad spaces characterized by highly regular geometries, such as regular concrete road tunnels. Moreover, SLAM requires that the surveyed geometry remain stable, and consequently, measurements in densely vegetated areas with strong winds that cause significant leaf movement should be avoided. The data processing approach of static laser scanners differs substantially from the process of producing the point cloud from iMMS instruments. The point cloud generated in a post-processing phase by the SLAM algorithm does not perfectly match the data acquired by the LiDAR sensor. First of all, the operator's trajectory is estimated by the SLAM algorithm by combining the raw data acquired by the LiDAR sensor and the IMU. Such an operation is performed in post-processing, and various system manufacturers and research teams have developed proprietary solutions to improve and optimize the estimation of the instrument's trajectory [56]. For example, the research group at the JRC of the European Commission has developed the local maps approach [57], which consists of \"a robust Global Matching technique focused on 3D mapping applications using laser range finders\". The method operates on the presumption that the projection of the observed coordinates along the gravity direction during the mapping process can identify locations. By aligning their 2D projective representations and utilizing the corresponding dimensional reduction, the relative poses between pairs of 3D point clouds are calculated in order to improve the trajectory evaluation performed by the SLAM algorithm. After the trajectory is estimated, the software generates the point cloud at the required resolution, taking into account any geometric constraints, which typically consist of control points. It is obvious that the quality of the point cloud model generated is directly correlated with the accuracy of the trajectory estimation provided by the instrument. Consequently, surveyors familiar with TLS devices may find it contradictory that remaining stationary with the iMMS device during the acquisition, for instance in a specific area of a building, significantly increases the amount of data to be processed but does not increase the density of the point cloud model that the system will generate at the conclusion of the post-processing process. Finally, we can conclude that the introduction of the SLAM solution has immediately represented a valuable aid in making surveying operations of large real estate complexes faster and more sustainable [58; 59; 60]. For the first SLAM-based systems, the most significant limitation was the high level of noise of the three-dimensional data and the geometric drifts affecting the trajectory estimated by the algorithm. For these reasons, SLAM devices have been utilized primarily in applications where the main goal was not to achieve high accuracy in three-dimensional surveying.