A terrain description method for traversability analysis based on elevation grid map
Terrain traversability analysis is a challenging problem for mobile robots to adapt to complex environments, including the detection of cluttered obstacles, potholes, or even slopes. With the accurate distance information, using distance sensors such as three-dimensional light detection and ranging...
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2018-01-01
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.1177/1729881417751530 |
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doaj-6db3604be8c34db8a04b8f8f0c13dbae2020-11-25T03:15:32ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142018-01-011510.1177/1729881417751530A terrain description method for traversability analysis based on elevation grid mapXiangrui Meng0Zhiqiang Cao1Shuang Liang2Lei Pang3Shuo Wang4Chao Zhou5 University of Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, China University of Chinese Academy of Sciences, Beijing, ChinaTerrain traversability analysis is a challenging problem for mobile robots to adapt to complex environments, including the detection of cluttered obstacles, potholes, or even slopes. With the accurate distance information, using distance sensors such as three-dimensional light detection and ranging (LiDAR) for terrain description becomes a preferred choice. In this article, a terrain description method for traversability analysis based on elevation grid map is presented. After the elevation grid map is generated, the ground is segmented with the aid of a height difference kernel and the non-ground grids in the map are then clustered. The terrain description features, including height index, roughness, and slope angle, are calculated and estimated. The slope angle is estimated using random sample consensus (RANSAC) and least squares method, and specifically, the roughness is combined to eliminate false slopes. Experimental results verified the effectiveness of the proposed method.https://doi.org/10.1177/1729881417751530 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xiangrui Meng Zhiqiang Cao Shuang Liang Lei Pang Shuo Wang Chao Zhou |
spellingShingle |
Xiangrui Meng Zhiqiang Cao Shuang Liang Lei Pang Shuo Wang Chao Zhou A terrain description method for traversability analysis based on elevation grid map International Journal of Advanced Robotic Systems |
author_facet |
Xiangrui Meng Zhiqiang Cao Shuang Liang Lei Pang Shuo Wang Chao Zhou |
author_sort |
Xiangrui Meng |
title |
A terrain description method for traversability analysis based on elevation grid map |
title_short |
A terrain description method for traversability analysis based on elevation grid map |
title_full |
A terrain description method for traversability analysis based on elevation grid map |
title_fullStr |
A terrain description method for traversability analysis based on elevation grid map |
title_full_unstemmed |
A terrain description method for traversability analysis based on elevation grid map |
title_sort |
terrain description method for traversability analysis based on elevation grid map |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2018-01-01 |
description |
Terrain traversability analysis is a challenging problem for mobile robots to adapt to complex environments, including the detection of cluttered obstacles, potholes, or even slopes. With the accurate distance information, using distance sensors such as three-dimensional light detection and ranging (LiDAR) for terrain description becomes a preferred choice. In this article, a terrain description method for traversability analysis based on elevation grid map is presented. After the elevation grid map is generated, the ground is segmented with the aid of a height difference kernel and the non-ground grids in the map are then clustered. The terrain description features, including height index, roughness, and slope angle, are calculated and estimated. The slope angle is estimated using random sample consensus (RANSAC) and least squares method, and specifically, the roughness is combined to eliminate false slopes. Experimental results verified the effectiveness of the proposed method. |
url |
https://doi.org/10.1177/1729881417751530 |
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