Terrain Classification for Mobile Robots on the Basis of Support Vector Data Description
- Authors
- Lee, Hyunsuk; Chung, Woojin
- Issue Date
- 9월-2018
- Publisher
- KOREAN SOC PRECISION ENG
- Keywords
- Mobile robot; Traversability analysis; Classification; Obstacle detection; Mapping
- Citation
- INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING, v.19, no.9, pp.1305 - 1315
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- INTERNATIONAL JOURNAL OF PRECISION ENGINEERING AND MANUFACTURING
- Volume
- 19
- Number
- 9
- Start Page
- 1305
- End Page
- 1315
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/73213
- DOI
- 10.1007/s12541-018-0154-4
- ISSN
- 2234-7593
- Abstract
- The ability to detect traversable terrains is essential for autonomous mobile robots to guarantee safe navigation. In this paper, we present a method for terrain classification for wheeled mobile robots. Our scope is limited to mobile service robots that are used for surveillance or delivery in semi-structured urban environments. A reliable terrain detection scheme is required for both indoor and outdoor applications anytime. A low-cost Lidar (Light detection and ranging) is adopted for terrain detection. To deal with intrinsic measurement errors and uncertainties of the Lidar, the classification criteria are trained through a supervised learning approach. Training data are obtained from manual driving at target environments. Various decision boundaries resulted from a variety of floor conditions, sensor types and robot platforms. The proposed terrain classification scheme is experimentally tested in success.
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Collections - College of Engineering > Department of Mechanical Engineering > 1. Journal Articles
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