NDLI: Satellite image based topological map building method for intelligent mobile robots

Content Provider	IEEE Xplore Digital Library
Author	Yu-Cheol Lee Christiand Wonpil Yu Sunghoon Kim
Copyright Year	2012
Description	Author affiliation: Department of Robot Cognition and System, Electronics and Telecommunications Research Institute (ETRI), 161 Gajeong-Dong, Yuseong-gu, Daejeon, 305-700, Korea (Yu-Cheol Lee)
Abstract	This paper presents an efficient method for building a topological map for robots in urban environments based on satellite image maps acquired from a geographic information system (GIS). In urban space, mobile robots need a special map, such as a topological map, to generate a path toward their goal. A topological map for mobile robot navigation should include semantic data, e.g., the width and type of road. We divide the satellite image based topological map building process into two steps. The first step is defining the topological map model to fit the mobile robot navigation in an urban environment. The second step is generating a topological map from existing satellite image maps downloaded from the GIS to reduce the cost and improve the accuracy in building the map. If a GIS-based topological map is constructed once, it is possible to use the map for the navigation of various robots as common spatial data. To validate the proposed mapping method, we show details of its implementation in map building as well as in a navigation experiment in real outdoor environments, such as a campus or city district.
Starting Page	867
Ending Page	872
File Size	1882627
Page Count	6
File Format	PDF
ISBN	9781467321198
ISSN	19310587
e-ISBN	9781467321181
DOI	10.1109/IVS.2012.6232295
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-06-03
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Global Positioning System Robot sensing systems Mobile robots Roads Satellites
Content Type	Text
Resource Type	Article

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