Human-Robot Interactive Learning Architecture using Ontologies and Symbol Manipulation

Alexandre Angleraud, Quentin Houbre, Ville Kyrki, Roel Pieters

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

5 Citations (Scopus)
155 Downloads (Pure)

Abstract

Robotic systems developed for support can provide assistance in various ways. However, regardless of the service provided, the quality of user interaction is key to adoption by the general public. Simple communication difficulties, such as terminological differences, can make or break the acceptance of robots. In this work we take into account these difficulties in communication between a human and a robot. We propose a system that allows to handle unknown concepts through symbol manipulation based on natural language interactions. In addition, ontologies are used as a convenient way to store the knowledge and reason about it. To demonstrate the use of our system, two scenarios are described and tested with a Care-O-Bot 4. The experiments show that confusions and difficulties in communication can effectively be resolved through symbol manipulation.

Original languageEnglish
Title of host publicationProceedings of the 27th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2018
PublisherIEEE
Pages384-389
Number of pages6
ISBN (Electronic)9781538679807
DOIs
Publication statusPublished - 6 Nov 2018
MoE publication typeA4 Article in a conference publication
EventIEEE International Symposium on Robot and Human Interactive Communication - Nanjing, China
Duration: 27 Aug 201831 Aug 2018
Conference number: 27

Conference

ConferenceIEEE International Symposium on Robot and Human Interactive Communication
Abbreviated titleRO-MAN
CountryChina
CityNanjing
Period27/08/201831/08/2018

Keywords

  • Robots
  • Cognition
  • Grounding
  • Ontologies
  • Knowledge based systems
  • Task analysis
  • Education

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