Contextual Knowledge Representation and Reasoning Models for Autonomous Robots
Résumé
To provide, anywhere and anytime, smart assistive services
to people, cognitive robots and agents need to be endowed
with advanced spatio-temporal knowledge representation and
reasoning capabilities. In this paper, a semantic approach for
cloud-assisted robotics integrating entities of the ambient environment is proposed. Its principle consists of advanced contextual knowledge representation and reasoning models based
on the hybridization of metric, topological and semantic information. A scenario dedicated to the cognitive assistance of
frail people is implemented and analyzed for validation purposes of the proposed approach.