The Impact of Personalization on Human-Robot Interaction in Learning Scenarios

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Nikhil Churamani, University of Hamburg
  • ,
  • Paul Anton, University of Hamburg
  • ,
  • Marc Brügger, University of Hamburg
  • ,
  • Erik Fließwasser, University of Hamburg
  • ,
  • Thomas Hummel, University of Hamburg
  • ,
  • Julius Mayer, University of Hamburg
  • ,
  • Waleed Mustafa, University of Hamburg
  • ,
  • Hwei Geok Ng, University of Hamburg
  • ,
  • Quan Nguyen, University of Hamburg
  • ,
  • Marcus Soll, University of Hamburg
  • ,
  • Sebastian Springenberg, University of Hamburg
  • ,
  • Sascha Griffiths, University of Hamburg
  • ,
  • Stefan Heinrich, University of Hamburg
  • ,
  • Nicolás Navarro-Guerrero
  • Erik Strahl, University of Hamburg
  • ,
  • Johannes Twiefel, University of Hamburg
  • ,
  • Cornelius Weber, University of Hamburg
  • ,
  • Stefan Wermter, University of Hamburg
Advancements in Human-Robot Interaction involve robots being more responsive and adaptive to the human user they are interacting with. For example, robots model a personalised dialogue with humans, adapting the conversation to accommodate the user's preferences in order to allow natural interactions. This study investigates the impact of such personalised interaction capabilities of a human companion robot on its social acceptance, perceived intelligence and likeability in a human-robot interaction scenario. In order to measure this impact, the study makes use of an object learning scenario where the user teaches different objects to the robot using natural language. An interaction module is built on top of the learning scenario which engages the user in a personalised conversation before teaching the robot to recognise different objects. The two systems, i.e.textbackslash with and without the interaction module, are compared with respect to how different users rate the robot on its intelligence and sociability. Although the system equipped with personalised interaction capabilities is rated lower on social acceptance, it is perceived as more intelligent and likeable by the users.
Original languageEnglish
Title of host publicationInternational Conference on Human-Agent Interaction (HAI)
Number of pages10
Place of publicationBielefeld, Germany
PublisherACM
Publication year17 Oct 2017
Pages171-180
ISBN (print)978-1-4503-5113-3
DOIs
Publication statusPublished - 17 Oct 2017
Externally publishedYes
Event5th International Conference on Human-Agent Interaction - Campus Bielefeld, Bielefeld, Germany
Duration: 17 Oct 201720 Oct 2017
http://hai-conference.net/hai2017/

Conference

Conference5th International Conference on Human-Agent Interaction
LocationCampus Bielefeld
LandGermany
ByBielefeld
Periode17/10/201720/10/2017
Internetadresse

    Research areas

  • ausrl

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