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Line segment-based fast 3D plane extraction using nodding 2D laser rangefinder

Published online by Cambridge University Press:  01 May 2014

Su-Yong An ,
Lae-Kyoung Lee  and
Se-Young Oh
Su-Yong An*
Affiliation:
Institute of Industrial Technology, Samsung Heavy Industries, Daejeon, 305-380, Korea
Lae-Kyoung Lee
Affiliation:
Department of Electrical Eng., Pohang University of Science and Technology (POSTECH), Pohang, Gyungbuk 790-784, Korea
Se-Young Oh
Affiliation:
Department of Electrical Eng., Pohang University of Science and Technology (POSTECH), Pohang, Gyungbuk 790-784, Korea
*
*Corresponding author. E-mail: hoppery0420@gmail.com
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Summary

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Three-dimensional (3D) data processing has applications in solving complex tasks such as object recognition, environment modeling, and robotic mapping and localization. Because using raw 3D data without preprocessing is very time-consuming, extraction of geometric features that describe the environment concisely is essential. In this sense, a plane can be a suitable geometric feature due to its simplicity of extraction and the abundance in indoor environments. This paper presents an online incremental plane extraction method using line segments for indoor environments. Our data collection system is based on a “nodding” laser scanner, so we exploit the incremental nature of its data acquisition in which physical rotation and 3D data processing are conducted in parallel. Line segments defined by two end points become supporting elements that comprise a plane, so a large proportion of scan points can be ignored once the line segments are extracted from each scan slice. This elimination of points reduces the algorithm complexity and computation time. Experiments with the tens of complete scan data sets which were acquired from a typical indoor environment demonstrated that our method was at least three times faster than the state-of-the-art methods.

Keywords

3D point cloudLaser scannerLine segmentPlane fitting

Information

Type
Articles
Information
Robotica , Volume 33 , Issue 8 , October 2015 , pp. 1751 - 1774
Copyright
Copyright © Cambridge University Press 2014 

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