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Autonomous Point Cloud Acquisition of Unknown Indoor Scenes

Applied Geotechnologies Group, Department Natural Resources and Environmental Engineering, Campus Lagoas-Marcosende, University of Vigo, CP 36310 Vigo, Spain
Fundación Centro Innovación Aeroespacial De Galicia, Rúa das Pontes 6, CP 36350 Nigrán, Spain
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(7), 250;
Received: 30 May 2018 / Revised: 18 June 2018 / Accepted: 24 June 2018 / Published: 27 June 2018
PDF [6066 KB, uploaded 27 June 2018]


This paper presents a methodology for the automatic selection of heuristic scanning positions in unknown indoor environments. The surveying is carried out by a robotic system following a stop-and-go procedure. Starting with a random scan position in the room, the point cloud is discretized in voxels and they are submitted to a two-step classification and are labelled as occupied, occluded, empty, window, door, or exterior based on a visibility analysis. The main objective of the methodology is to obtain a complete point cloud of the indoor space and accordingly, the next best position is the scan position minimizing occluded voxels. Because the method locates doors and windows, the room can be delimited and the scan can continue for adjacent rooms. This approach has been tested in a real case study, in which three scans were developed. View Full-Text
Keywords: autonomous navigation; spatial analysis; ray tracing; 3D digitalization; NBV autonomous navigation; spatial analysis; ray tracing; 3D digitalization; NBV

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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González-de Santos, L.M.; Díaz-Vilariño, L.; Balado, J.; Martínez-Sánchez, J.; González-Jorge, H.; Sánchez-Rodríguez, A. Autonomous Point Cloud Acquisition of Unknown Indoor Scenes. ISPRS Int. J. Geo-Inf. 2018, 7, 250.

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