Hee-Won Chae

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Depth sensors have been increasingly used for object recognition in recent years. However, it is very challenging for simultaneous localization and mapping (SLAM) to make use of the forward scenes from a depth sensor. To this end, we introduce the object recognition framework for SLAM in indoor environments based on the extraction of an object-level(More)
Place recognition is widely used in the loop closure detection in SLAM. The current approach to place recognition is based on RGB images, but there are relatively few place recognition studies using a point cloud. This study presents the place recognition method based on the surface graph. The proposed method clusters the surfaces in the point cloud and(More)
This paper proposes a point feature-based outdoor SLAM method using only omnidirectional LIDAR. 3D local occupancy grid mapping and ground plane classification are conducted as a pre-process to refine the point cloud. Then uncertain objects are clustered with Euclidean distance. For applications in rural environments, point features are utilized because(More)
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