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In this paper, we present a vision-based metric/topological approach for the Simultaneous Localization and Mapping (SLAM) problem. Similar to recent works on metric/topological SLAM (MT SLAM) where the map is represented as a graph whose nodes are submaps and edges are relative transformations between submaps, we propose a graphical model for vision-based MT SLAM that estimates the hybrid robot pose...
This paper addresses a navigation method which copes with dynamic environments, e.g. objects moving in the environment and environment changes. Because many vision-based navigation methods mainly focus on finding consistent corresponding parts with one of the database images, dynamic environments can cause the failure of autonomous navigation due to visual occlusion. To solve these problems, we propose...
In this paper, we present a robust simultaneous localization and mapping (SLAM) framework using a single camera catadioptric stereo system composed of vertically aligned two hyperboloidal mirrors and a CCD camera. In the SLAM, conventional stereo cameras have some problems due to their narrow field of view, for example, the data association problem which occurs in the featureless homogeneous regions...
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