A Guided Performance Interface for Augmenting Social Experiences with an Interactive Animatronic Character


  • Seema Patel noreply@aaai.org
  • William Bosley Carnegie Mellon University
  • David Culyba Carnegie Mellon University
  • Sabrina A. Haskell Carnegie Mellon University
  • Andrew Hosmer noreply@aaai.org
  • T. J. Jackson noreply@aaai.org
  • Shane J. M. Liesegang noreply@aaai.org
  • Peter Stepniewicz noreply@aaai.org
  • James Valenti Carnegie Mellon University
  • Salim Zayat Carnegie Mellon University
  • Brenda Harger Carnegie Mellon University




Entertainment animatronics has traditionally been a discipline devoid of interactivity. Previously, we brought interactivity to this field by creating a suite of content authoring tools that allowed entertainment artists to easily develop fully autonomous believable experiences with an animatronic character. The recent development of a Guided Performance Interface (GPI) has allowed us to explore the advantages of nonautonomous control. Our new hybrid approach utilizes an autonomous AI system to control low-level behaviors and idle movements, which are augmented by high-level processes (such as complex conversation) issued by a human operator through the GPI. After observing thousands of interactions between human guests and our animatronic character at SIGGRAPH 2005's Emerging Technologies Exhibition, we strongly feel that both autonomy and guided performance have important roles in interactive, entertainment robotics. Together, the autonomous system and the new Guided Performance Interface allow guests to experience extremely rich, believable, social experiences with robots using technology available today.




How to Cite

Patel, S., Bosley, W., Culyba, D., Haskell, S., Hosmer, A., Jackson, T. J. ., Liesegang, S., Stepniewicz, P., Valenti, J., Zayat, S., & Harger, B. (2021). A Guided Performance Interface for Augmenting Social Experiences with an Interactive Animatronic Character. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 2(1), 72-79. https://doi.org/10.1609/aiide.v2i1.18749