Ontologenius : A long-term semantic memory for robotic agents

Guillaume Sarthou 1 Aurélie Clodic 2 Rachid Alami 1
1 LAAS-RIS - Équipe Robotique et InteractionS
LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]
2 LAAS-IDEA - Service Informatique : Développement, Exploitation et Assistance
LAAS - Laboratoire d'analyse et d'architecture des systèmes [Toulouse]
Abstract : In this paper we present Ontologenius, a semantic knowledge storage and reasoning framework for autonomous robots. More than a classic ontology software to query a knowledge base and a first-order internal logic as it can be done for web-semantics, we propose with Ontologenius features adapted to a robotic use including human-robot interaction. We introduce the ability to modify the knowledge base during execution, whether through dialogue or geometric reasoning, and keep these changes even after the robot is powered off. Since Ontologenius was developed to be used by a robot which interacts with humans, we have endowed the system with ability to perform attributes and properties generalization and with the possibility to model and estimate the semantic memory of a human partner and to implement theory of mind processes. This paper presents the architecture and the main features of Ontologenius as well as examples of its use in robotics applications.
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Guillaume Sarthou, Aurélie Clodic, Rachid Alami. Ontologenius : A long-term semantic memory for robotic agents. IEEE International Conference on Robot & Human Interactive Communication (IEEE Ro-MAN 2019), Oct 2019, New Delhi, India. ⟨hal-02283342⟩

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