Semantic Maps for Robotics
نویسندگان
چکیده
Most mobile robotic systems use internal representations of the gathered information that is not intuitively understandable by humans and that is inadequate for learning from commonly available sources. The combination of object/place classification and common-sense knowledge to semantic maps found its way into indoor semantic mapping approaches in order to improve human-robot interaction. The aim is to pass complex task settings to the robot, so that it guides the search for the solution itself. In this paper, we present a common formal definition of semantic robotic maps as an extension of hybrid maps introduced by Buschka [1]. We discuss different criteria for design, classification and challenges of semantic maps. Furthermore, we present an evaluation template based on the definition, properties and challenges of semantic maps for three well known semantic mapping approaches.
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