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Although robot navigation in indoor environments has achieved great success, robots are unable to fully navigate these spaces without the ability to operate elevators, including those which the robot has not seen before. In this paper, we focus on the key challenge of autonomous interaction with an unknown elevator button panel. A number of factors, such as lack of useful 3D features, variety of elevator...
The object-based attention theory has shown that perception processes only select relevant objects of the world which are then represented for action. Thus this paper proposes a novel computational method of robotic visual perception based on the object-based attention mechanism. It involves three modules: pre-attentive processing, attentional selection and perception learning. Visual scene is firstly...
Image ground segmentation is an important task in the area of computer vision for the robot navigation because the ground region is often taken as the traversable terrain. In this paper, we propose a learning-based method for image ground segmentation which applies the Adaboost learning method to combine multiple cues for detection of the ground region in an image. Firstly, an image is segmented into...
Many terrains in outdoor robot navigation problems have paths that are distinct and continuous compared to the non-traversable regions. In image space these paths correspond to continuous segments that can be thought of as clusters embedded in image feature space. These segments very often translate directly to traversable ground plane. In this paper we build the intuition for semi-supervised methods...
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