Examination of Indoor Mobile Mapping Systems in a Diversified Internal/External Test Field

Nowadays, simultaneous localization and mapping (SLAM) algorithms support several commercial sensors which have recently been introduced to the market, and, like the more common mobile mapping systems (MMSs), are designed to acquire three-dimensional and high-resolution point clouds. The new systems are said to work both in external and internal environments, and completely avoid the use of targets and control points. The possibility of increasing productivity in three-dimensional digitization projects is fascinating, but data quality needs to be carefully evaluated to define appropriate fields of application. The paper presents the analytical measurement principle of these indoor mobile mapping systems (IMMSs) and the results of some tests performed on three commercial systems. A common test field was defined in order to acquire comparable data. By taking the already available terrestrial laser scan survey as the ground truth, the datasets under examination were compared with the reference and some assessments are presented which consider both quantitative and qualitative aspects. Geometric deformation in the final models was computed using the so-called Multiscale Model to Model Cloud Comparison (M3C2) algorithm. Cross sections and cloud to mesh (C2M) distances were also employed for a more detailed analysis. The real usability assessment is based on the features of recognizability, double surface evidence, and visualization effectiveness. For these evaluations, comparative images and tables are presented.