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ORO, a knowledge management platform for cognitive architectures in robotics

Séverin Lemaignan, Raquel Ros, Lorenz Mösenlechner, Rachid Alami, Michael Beetz

Year
2010
Citations
143

Abstract

This paper presents an embeddable knowledge processing framework, along with a common-sense ontology, designed for robotics. We believe that a direct and explicit integration of cognition is a compulsory step to enable human-robots interaction in semantic-rich human environments like our houses. The OpenRobots Ontology (ORO) kernel allows to turn previously acquired symbols into concepts linked to each other. It enables in turn reasoning and the implementation of other advanced cognitive functions like events, categorization, memory management and reasoning on parallel cognitive models. We validate this framework on several cognitive scenarii that have been implemented on three different robotic architectures.

Keywords

Computer scienceCategorizationCognitionOntologyCognitive roboticsCognitive architectureArtificial intelligenceRoboticsRobotCognitive model

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