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2018 | OriginalPaper | Chapter

A Ground Segmentation Method Based on Gradient Fields for 3D Point Clouds

Authors : Hoang Vu, Hieu Trong Nguyen, Phuong Chu, Seoungjae Cho, Kyungeun Cho

Published in: Advances in Computer Science and Ubiquitous Computing

Publisher: Springer Singapore

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Abstract

In order to navigate in an unknown environment, autonomous robots must distinguish traversable ground regions from impassible obstacles. Thus, ground segmentation is a crucial step for handling this issue. This study proposes a new ground segmentation method combining of two different techniques: gradient threshold segmentation and mean height evaluation. Ground regions near the center of the sensor are segmented using the gradient threshold technique, while sparse regions are segmented using mean height evaluation. The main contribution of this study is a new ground segmentation algorithm that can be applied to various 3D point clouds. The processing time is acceptable and allows real-time processing of sensor data.

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Metadata
Title
A Ground Segmentation Method Based on Gradient Fields for 3D Point Clouds
Authors
Hoang Vu
Hieu Trong Nguyen
Phuong Chu
Seoungjae Cho
Kyungeun Cho
Copyright Year
2018
Publisher
Springer Singapore
Book
Advances in Computer Science and Ubiquitous Computing

Print ISBN: 978-981-10-7604-6

Electronic ISBN: 978-981-10-7605-3

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-981-10-7605-3_64