Abstract
Nowadays, the availability of fast data acquisition systems based on mobile and handheld laser scanning platform are increasing in popularity due to their rapidity in data acquisition of large areas. BIM and HBIM based modelling can primary benefit of this new acquisition methods speeding up the so called “Scan-to-BIM” procedure. However, point clouds derived from Mobile Mapping Systems (MMS) compared to traditional static laser scanning acquisition presents some disadvantages: (i) point clouds are more noisy, (ii) generally less dense and (iii) some drift effects can be presents inside the data due to data registration. For those reason, in order to obtain a point cloud to be effectively used for modelling purposes a careful planning of the acquisition has to be taken into account. This paper, presents a methodology for optimal MMS path design according to some predefined target in terms of point density and point cloud completeness. In order to optimize the scanning path a simulation is carried out to define the best scanning configuration. In this paper the developed methodology is tested on a real case study: the outdoor of the main pavilion of the Politecnico di Milano – Polo Territoriale di Lecco.
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Acknowledgements
Research leading to this results is partially funded by Regione Lombardia - Bando “Smart Living: integrazione fra produzione servizi e tecnologia nella filiera costruzioni-legno-arredo-casa” approvato con d.d.u.o. n.11672 dell’15 novembre 2016 nell’ambito del progetto “HOMeBIM liveAPP: Sviluppo di una Live APP multi-utente della realtà virtuale abitativa 4D per il miglioramento di comfort-efficienza-costi, da una piattaforma cloud che controlla nel tempo il flusso BIM-sensori – ID 379270”.
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Previtali, M., Banfi, F., Brumana, R. (2020). Handheld 3D Mobile Scanner (SLAM): Data Simulation and Acquisition for BIM Modelling. In: Parente, C., Troisi, S., Vettore, A. (eds) R3 in Geomatics: Research, Results and Review. R3GEO 2019. Communications in Computer and Information Science, vol 1246. Springer, Cham. https://doi.org/10.1007/978-3-030-62800-0_20
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