Efficient, Situated and Ontology based Referring Expression Generation for Human-Robot collaboration - Archive ouverte HAL
Conference Papers Year : 2020

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

Abstract

In Human-Robot Interaction (HRI), ensuring non-ambiguous 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.
Fichier principal
Vignette du fichier
roman_2020_v2.pdf (3.95 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-02922098 , version 1 (25-08-2020)
hal-02922098 , version 2 (07-03-2021)

Identifiers

Cite

Guilhem Buisan, Guillaume Sarthou, Arthur Bit-Monnot, Aurélie Clodic, Rachid Alami. Efficient, Situated and Ontology based Referring Expression Generation for Human-Robot collaboration. The 29th IEEE International Conference on Robot & Human Interactive Communication ( RO-MAN), Aug 2020, Naples (on line), Italy. pp.349-356, ⟨10.1109/RO-MAN47096.2020.9223485⟩. ⟨hal-02922098v2⟩
323 View
211 Download

Altmetric

Share

More