Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/31474
Title: On-line segment-based map building via integration of fuzzy systems and clustering algorithms
Authors: Ip, YL
Rad, AB
Wong, YK
Keywords: Fuzzy clustering
Fuzzy systems
Mobile robots
Segment-based map building
Issue Date: 2005
Source: Journal of intelligent and fuzzy systems, 2005, v. 16, no. 3, p. 201-212 How to cite?
Journal: Journal of Intelligent and Fuzzy Systems 
Abstract: This paper presents a segment-detection and grouping scheme that allows incremental and on-line learning of indoor environment maps by mobile robots. The proposed algorithm is based on authors' earlier work of modeling the environment by Enhanced Adaptive Fuzzy Clustering (EAFC) algorithm along with Noise Clustering (NC). In this study, the modeling is refined by first dividing the world into discrete regions as local models. Then, the line segments in local and global models are grouped together by a hierarchical fuzzy system. Adjusting the membership functions that establish the grouping criteria controls the degree of approximation in such combination. The presented map building method for modeling an indoor office environment has successfully been implemented in real-time and tested on Pioneer 2DX mobile robot equipped with sonar sensors. The experimental studies demonstrate improved performance through continuous maps that are obtained by adopting the fuzzy system during the grouping of line segments within local and global models.
URI: http://hdl.handle.net/10397/31474
ISSN: 1064-1246
Appears in Collections:Journal/Magazine Article

Access
View full-text via PolyU eLinks SFX Query
Show full item record

Page view(s)

33
Last Week
0
Last month
Checked on Sep 17, 2017

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.