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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

References

Baltes, J., Tu, K. Y., Sadeghnejad, S. & Anderson, J. 2017. HuroCup: competition for multi-event humanoid robot athletes. The Knowledge Engineering Review, 32, 1–14.Google Scholar
Baltes, J. 2018. Call for Participation IEEE IROS 2018 Humanoid Application Challenge-Robot Magic Show. https://bit.ly/2JjeMlz (Accessed 17 March 2019).Google Scholar
Baltes, J., Sun, Y. & Moon, H. 2018. 2017 competitions: magical, manipulation, mercurial robots [competitions]. IEEE Robotics & Automation Magazine 25, 8–15.CrossRefGoogle Scholar
Costa, P. & McCrae, R. 1999. A five-factor theory of personality. The Five-Factor Model of Personality: Theoretical Perspectives 2, 51–87.Google Scholar
Lapeyre, M., Rouanet, P., Grizou, J., Nguyen, S., Depraetre, F., Le Falher, A. & Oudeyer, P. Y. 2014. Poppy project: open-source fabrication of 3D printed humanoid robot for science, education and art. In Digital Intelligence 2014, 6.Google Scholar
Moon, H., Sun, Y., Baltes, J. & Kim, S. 2017. The IROS 2016 competitions [competitions]. IEEE Robotics & Automation Magazine 24, 20–29.CrossRefGoogle Scholar
Morris, K. J., Samonin, V., Anderson, J., Lau, M. C. & Baltes, J. 2018a. Robot magic: a robust interactive humanoid entertainment robot. In International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, 245–256.Google Scholar
Morris, K. J., Anderson, J., Lau, M. C. & Baltes, J. 2018b. Interaction and learning in a humanoid robot magic performance. In 2018 AAAI Spring Symposium Series.Google Scholar
Robotics, Seed. 2019. RH2D MANIPULATOR. http://www.seedrobotics.com/rh2d-manipulator.html (Accessed 17 March 2019).Google Scholar
Simon, T., Joo, H., Matthews, I. & Sheikh, Y. 2017. Hand keypoint detection in single images using multiview bootstrapping. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 1145–1153. References ‘Simon et al. (2017)’ were identical in the reference list, so the latter has been deleted to avoid duplication and subsequent references and the citations have been renumbered. Please check and confirm this was done correctly.CrossRefGoogle Scholar
Soegaard, M. and Dam, R. F. 2013. The Encyclopedia of Human-Computer Interaction, 2nd edition. The Interaction Design Foundation.Google Scholar
Yang, J., Jeong, J. & Baltes, J. 2019. Humanoid robot magic: various responses and communication. In Proceedings of the 25th International Symposium on Electronic Art – ISEA 2019 ‘Lux Aeterna’, 73–78.Google Scholar