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Robot magic show: human–robot interaction

Part of: Robot Athletes and Entertainers

Published online by Cambridge University Press:  07 April 2020

Jaesik Jeong ,
Jeehyun Yang Open the ORCID record for Jeehyun Yang [Opens in a new window]  and
Jacky Baltes
Jaesik Jeong
Affiliation:
National Taiwan Normal University, 106, Heping E. Road, Sec. 1, Taipei City, 10610, Taiwan, e-mails: [email protected], [email protected], [email protected]
Jeehyun Yang
Affiliation:
National Taiwan Normal University, 106, Heping E. Road, Sec. 1, Taipei City, 10610, Taiwan, e-mails: [email protected], [email protected], [email protected]
Jacky Baltes
Affiliation:
National Taiwan Normal University, 106, Heping E. Road, Sec. 1, Taipei City, 10610, Taiwan, e-mails: [email protected], [email protected], [email protected]
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Abstract

The use of robots in performance arts is increasing. But, it is hard for robots to cope with unexpected circumstances during a performance, and it is almost impossible for robots to act fully autonomously in such situations. IROS-HAC is a new challenge in robotics research and a new opportunity for cross-disciplinary collaborative research. In this paper, we describe a practical method for generating different personalities of a robot entertainer. The personalities are created by selecting speech or gestures from a set of options. The selection uses roulette wheel selection to select answers that are more closely aligned with the desired personality. In particular, we focus on a robot magician, as a good magic show includes good interaction with the audience and it may also include other robots and performers. The magician with a variety of personalities increased the audience immersion and appreciation and maintained the audience’s interest. The magic show was awarded first prize in the competition for a comprehensive evaluation of technology, story, and performance. This paper contains both the research methodology and a critical evaluation of our research.

Type
Research Article
Information
The Knowledge Engineering Review , Volume 35 , 2020 , e15
Copyright
© Cambridge University Press, 2020

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Footnotes

*

The two authors contributed equally to this paper

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