Semantic management of human-robot interaction in ambient intelligence environments using N-ary ontologies

Abstract

In this paper, we present a semantic framework that is intended to enable natural interactions between ubiquitous robots and humans in Ambient Intelligence (AmI) environments. The main contribution of this paper is the extension of the core of the Narrative Knowledge Representation Language (NKRL) framework with semantic modules to allow on one hand, converting robot interactions into formal n-ary semantic annotations, and on the other hand, making semantic inferences for: (i) driving the human-robot dialogue, (ii) inferring the spatio-temporal context of the overall dialogue and (iii) mapping the inferred context with the actions that should be triggered in the AmI environment. A scenario dedicated to the monitoring and cognitive assistance of elderly people is implemented and discussed for validation purposes of the proposed framework.