Efficient, Situated and Ontology based Referring Expression Generation for Human-Robot collaboration

In Human-Robot Interaction (HRI), ensuring nonambiguous communication between the robot and the human is a key point for carrying out fluently a collaborative task. With this work, we propose a method which allows the robot to generate the optimal set of assertions that are necessary in order to produce an unambiguous reference. In this paper, we present a novel approach to the Referring Expression Generation (REG) problem and its integration into a robotic system. Our method is a domain-independent approach based on an ontology as a knowledge base. We show how this generation can be performed on an ontology which is not dedicated to this task. We then validate our method through simulated situations, compare it with state of the art approach and on a real robotic system.