Interaction and learning in a humanoid robot magic performance

Kyle Morris, John Anderson, Meng Cheng Lau, Jacky Baltes

研究成果: 會議貢獻類型會議論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

Magicians have been a source of entertainment for many centuries, with the ability to play on human bias, and perception to create an entertaining experience. There has been rapid growth in robotics throughout industrial applications; where primary challenges include improving human-robot interaction, and robotic perception. Despite preliminary work in expressive AI, which aims to use AI for entertainment; there has not been direct application of fully embodied autonomous agents (vision, speech, learning, planning) to entertainment domains. This paper describes preliminary work towards the use of magic tricks as a method for developing fully-embodied autonomous agents. A card trick is developed requiring vision, communication, interaction, and learning capabilities all of which are coordinated using our script representation. Our work is evaluated quantitatively through experimentation, and qualitatively through acquiring 2nd place at the 2016 IROS Humanoid Application Challenge. A video of the live performance can be found at https://youtu.be/OMpcmcPWAVM.

原文英語
頁面578-581
頁數4
出版狀態已發佈 - 2018
事件2018 AAAI Spring Symposium - Palo Alto, 美国
持續時間: 2018 三月 262018 三月 28

會議

會議2018 AAAI Spring Symposium
國家/地區美国
城市Palo Alto
期間2018/03/262018/03/28

ASJC Scopus subject areas

  • 人工智慧

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