Ground Segmentation From Large-Scale Terrestrial Laser Scanner Data of Industrial Environments
Mikhail Giorgini, Federico Barbieri, Jacopo Aleotti
Abstract
In many 3-D perception applications, ground segmentation is a necessary preprocessing phase together with point cloud cleaning and outlier removal. This letter presents a method for ground segmentation in large-scale point clouds of industrial environments acquired using a terrestrial laser scanner (TLS). TLSs provide high-precision, dense 3-D measurements, and therefore, such instruments are becoming the state of the art technology for surveying tasks. In contrast to many previous works, where ground segmentation has been investigated using a single scan (e.g., in LiDAR-equipped vehicles), experiments have been performed in large-scale point clouds that contain over 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">10</sup> points measured from multiple scan stations. The proposed solution is based on a robust estimation of points belonging to the ground below each scan station and it can be applied even in challenging scenarios with nonplanar regions.
BibTeX
@inproceedings{ral2017_groundsegmentati,
title = {Ground Segmentation From Large-Scale Terrestrial Laser Scanner Data of Industrial Environments},
author = {Mikhail Giorgini and Federico Barbieri and Jacopo Aleotti},
booktitle = {RA-L 2017},
year = {2017}
}