Semantic framework to enhance human-robot interaction using EKRL
Omar Adjali, Amar Ramdane-Chérif · 2017
This paper describes a semantic framework that demonstrates an approach for modelling and reasoning based on environment knowledge representation language (EKRL) to enhance interaction between robots and their environment. Unlike EKRL, standard Binary approaches like OWL language fails to represent knowledge in an expressive way. We show in this work how to: model environment and interaction in an expressive way with first-order and second-order EKRL data-structures, and reason for decision-making thanks to inference capabilities based on a complex unification algorithm.