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.

In this paper, the problem of endowing ubiquitous robots with cognitive capabilities for recognizing emotions, sentiments, affects and moods of humans, in their context, is studied. A hybrid approach based on multilayer perceptron (MLP) neural network and n-ary ontologies for emotion-aware robotic systems is proposed. In particular, an algorithm based on the hybrid-level fusion, an expressive emotional knowledge representation and reasoning model are introduced to recognize complex and non-observable emotional context of the user. Empirical experiments on real-world dataset corroborate its effectiveness.