Coarse-to-Fine Global Localization for Mobile Robots with Hybrid Maps of Objects and Spatial Layouts

Title
Coarse-to-Fine Global Localization for Mobile Robots with Hybrid Maps of Objects and Spatial Layouts
Authors
박순용정호원박성기
Keywords
navigation; object recognition; hybrid map; localization
Issue Date
2009-10
Publisher
The 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems
Citation
, 3993-4000
Abstract
This paper proposes a novel global localization approach that uses hybrid maps of objects and spatial layouts. We model indoor environments using the following visual cues from a stereo camera: local invariant features for object recognition and their 3D positions for object location representation. We also use a 2D laser range finder. Therefore, we can build a hybrid local node for a topological map that is composed of an object location map and a spatial layout map. Based on this modeling, we suggest a coarse-to-fine strategy for the global localization. The coarse pose is obtained by means of object recognition and point cloud fitting, and then its fine pose is estimated with a probabilistic scan matching algorithm. With real experiments, we show that our proposed method can be an effective global localization algorithm.
URI
http://pubs.kist.re.kr/handle/201004/36142
Appears in Collections:
KIST Publication > Conference Paper
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