Contextual Knowledge Representation and Reasoning Models for Autonomous Robots

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.