Abstract
Total and automatic digitalization of indoor spaces in 3D implies a great advance in building maintenance and construction tasks, which currently require visits and manual works. Terrestrial laser scanners (TLS) have been widely used for these tasks, although the acquisition methodology with TLS systems is time consuming, and each point cloud is acquired in a different coordinate system, so the user has to post-process the data to clean and get a unique point cloud of the whole scenario. This paper presents a solution for the automatic data acquisition and registration of point clouds from indoor scenes, designed for point clouds acquired with a terrestrial laser scanner (TLS) mounted on an unmanned ground vehicle (UGV). The methodology developed allows the generation of one complete dense 3D point cloud consisting of the acquired point clouds registered in the same coordinate system, reaching an accuracy below 1 cm in section dimensions and below 1.5 cm in walls thickness, which makes it valid for quality control in building works. Two different study cases corresponding to building works were chosen for the validation of the method, showing the applicability of the methodology developed for tasks related to the control of the evolution of the construction.
Highlights
The demand for 3D models of building interiors has grown in the recent years due to (1) the need to have as-built 3D models available for tasks related to planning and maintenance in buildings and (2) the proliferation of the building information modelling (BIM) standard [1,2,3,4]
Terrestrial laser scanners (TLS) have been widely used for these tasks, the acquisition methodology with TLS systems is time consuming, and each point cloud is acquired in a different coordinate system, so the user has to post-process the data to clean and get a unique point cloud of the whole scenario
This paper presents a solution for the automatic data acquisition and registration of point clouds from indoor scenes, designed for point clouds acquired with a terrestrial laser scanner (TLS) mounted on an unmanned ground vehicle (UGV)
Summary
The demand for 3D models of building interiors has grown in the recent years due to (1) the need to have as-built 3D models available for tasks related to planning and maintenance in buildings and (2) the proliferation of the building information modelling (BIM) standard [1,2,3,4]. This method reaches sufficient results only when the overlap between scans is good To solve this problem, [18] presented a novel methodology to register outdoor and indoor point clouds using a two-step process: first, they extracted common features using the RGB information acquired by a digital camera and they refined the alignment using iterative closest points (ICP) or planes matching techniques, that work properly even when the overlap between scans is poor. Both methods are robust and suitable for indoor and outdoor scenarios, but a hybrid calibrated system composed by an RGB camera and a laser scanner is mandatory. Target Need Image Need Only Pairwise Registration Minimum Overlap Required Noise Sensitive
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