Park, Soonyong Cheong, Howon Park, Sung-Kee 2024-01-19T13:08:23Z 2024-01-19T13:08:23Z 2022-03-07 2009 https://pubs.kist.re.kr/handle/201004/116061 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. English IEEE Coarse-to-Fine Global Localization for Mobile Robots with Hybrid Maps of Objects and Spatial Layouts Conference 10.1109/IROS.2009.5354193 1 IEEE RSJ International Conference on Intelligent Robots and Systems, pp.3993 - 4000 IEEE RSJ International Conference on Intelligent Robots and Systems 3993 4000 US St Louis, MO 2009-10-10 2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS 000285372902031 2-s2.0-76249132012 Proceedings Paper