Daniel Di Marco

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—The vision of the RoboEarth project is to design a knowledge-based system to provide web and cloud services that can transform a simple robot into an intelligent one. In this work we describe the RoboEarth semantic mapping system. The semantic map is composed of (1) an ontology to code the concepts and relations in maps and objects, and (2) a SLAM map(More)
— In this paper we explore how a visual SLAM system and a robot knowledge base can mutually benefit from each other. The object recognition and mapping methods are used for grounding abstract knowledge and for creating a semantically annotated environment map that is available for reasoning. The knowledge base allows to reason about which object types are(More)
The ability of reusing existing task execution plans is an important step towards autonomous behavior. Today, the reuse of sophisticated services allowing robots to act autonomous is usually limited to identical robot platforms and to very similar application scenarios. The approach presented in this paper proposes a way to mitigate this limitation by(More)
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