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Social Human-Robot Interaction is Personalized Interaction

 
: Pollmann, Kathrin; Ziegler, Daniel

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Volltext urn:nbn:de:0011-n-6154849 (225 KByte PDF)
MD5 Fingerprint: 5fcd0121517a0292cc4217cb82f58618
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Erstellt am: 28.11.2020


Pollmann, Kathrin (Ed.); Ziegler, Daniel (Ed.) ; Fraunhofer-Institut für Arbeitswirtschaft und Organisation -IAO-, Stuttgart:
Workshop on Behavioral Patterns and Interaction Modelling for Personalized Human-Robot Interaction 2020. Proceedings : Workshop at the 15th Annual ACM/IEEE International Conference on Human Robot Interaction, March 23, 2020, Cambridge, UK
Stuttgart: Fraunhofer IAO, 2020
S.4-7
Workshop on Behavioral Patterns and Interaction Modelling for Personalized Human-Robot Interaction <2020, Cambridge/cancelled>
International Conference on Human-Robot Interaction (HRI) <15, 2020, Cambridge/cancelled>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Mensch-Technik-Interaktion: "Technik zum Menschen bringen"-Roboter für Assistenzfunktionen: Interaktionsstrategien; 16SV7941; nika
Nutzerzentrierte Interaktionsgestaltung für Kontextsensitive und Akzeptable Roboter
Englisch
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IAO ()

Abstract
Previous research has indicated that robots that show social behavior when interacting with humans are better accepted. In this paper we argue that the robot behavior does not only need to be social, but also tailored to individual user characteristics, in order to be experienced as positive by the user in long-term use. To realize such personalized human-robot interactions, we need to identify differences among users, represent them in a user model and develop a number of design variants for the robot behavior. We propose to augment the conventional human-centered design process to focus on obtaining the relevant user information and creating matching design variants. We describe the different phases of the HCD4Personalization and illustrate them with examples from the NIKA project which is aimed at developing acceptable and positive interaction strategies for social robots that support older adults in their homes.

: http://publica.fraunhofer.de/dokumente/N-615484.html