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Title: A novel culture-dependent gesture selection system for a humanoid robot performing greeting interaction
Authors: Trovato, Gabriele
Do, Martin
Kuramochi, Masuko
Zecca, Massimiliano
Terlemez, Omer
Asfour, Tamim
Takanishi, Atsuo
Keywords: Social Robotics
Issue Date: 2014
Publisher: © Springer-Verlag
Citation: TROVATO, G. ... et al, 2014. A novel culture-dependent gesture selection system for a humanoid robot performing greeting interaction. IN: Beetz, M., Johnston, B. and Williams, M.-A. (eds). Social Robotics: Proceedings of the 6th International Conference ICSR 2014, 27th-29th October 2014, Sydney, Australia. Springer-Verlag, pp.340-349.
Series/Report no.: Lecture Notes in Computer Science;8755
Abstract: In human-robot interaction, it is important for the robots to adapt to our ways of communication. As humans, rules of non-verbal communication, including greetings, change depending on our culture. Social robots should adapt to these specific differences in order to communicate effectively, as a correct way of approaching often results into better acceptance of the robot. In this study, a novel greeting gesture selection system is presented and an experiment is run using the robot ARMAR-IIIb. The robot performs greeting gestures appropriate to Japanese culture; after interacting with German participants, the selection should become appropriate to German culture. Results show that the mapping of gesture selection evolves successfully.
Description: This definitive published version of this article is available from: http://dx.doi.org/10.1007/978-3-319-11973-1_35
Sponsor: This study was conducted as part of the Research Institute for Science and Engineering, Waseda University, and as part of the humanoid project at the Humanoid Robotics Institute, Waseda University. The experiment was carried out in Karlsruhe Institute of Technology, thanks to InterACT, the Waseda/KIT exchange network.
Version: Accepted for publication
DOI: 10.1007/978-3-319-11973-1_35
URI: https://dspace.lboro.ac.uk/2134/17559
Publisher Link: http://dx.doi.org/10.1007/978-3-319-11973-1_35
ISBN: 9783319119724
ISSN: 0302-9743
Appears in Collections:Published Articles (Mechanical, Electrical and Manufacturing Engineering)

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