Interaction and Learning in a Humanoid Robot Magic Performance

Magicians have been a source of entertainment formany centuries, with the ability to play on human bias,and perception to create an entertaining experience.There has been rapid growth in robotics throughoutindustrial applications; where primary challenges in-clude improving human-robot interaction, and roboticperception. Despite preliminary work in expressive AI,which aims to use AI for entertainment; there has notbeen direct application of fully embodied autonomousagents (vision, speech, learning, planning) to enter-tainment domains. This paper describes preliminarywork towards the use of magic tricks as a methodfor developing fully-embodied autonomous agents. Acard trick is developed requiring vision, communica-tion, interaction, and learning capabilities all of whichare coordinated using our script representation. Ourwork is evaluated quantitatively through experimen-tation, and qualitatively through acquiring 2nd placeat the 2016 IROS Humanoid Application Challenge.A video of the live performance can be found at https://youtu.be/OMpcmcPWAVM.