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Human robot interaction is an emerging area of research, where human understandable robotic representations can play a major role. Knowledge of semantic labels of places can be used to effectively communicate with people and to develop efficient navigation solutions in complex environments. In this paper, we propose a new approach that enables a robot to learn and classify observations in an indoor...
Extending metric space representations of an environment with other high level information, such as semantic and topological representations enable a robotic device to efficiently operate in complex environments. This paper proposes a methodology for a robot to classify indoor environments into semantic categories. Classification task, using data collected from a laser range finder, is achieved by...
Relating information originating from disparate sensors without any attempt to model the environment or the behaviour of any particular object within it is a challenging task. Inspired by human perception, the focus of this paper will be on observing objects moving in space using sensors that operate based on different physical principles and the fact that motion has in principle, greater power to...
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