Towards Embedding Dynamic Personas in Interactive Robots: Masquerading Animated Social Kinematics (MASK)

Jeongeun Park, Taemoon Jeong, Hyeonseong Kim, Taehyun Byun, Seungyoon Shin +5 more
3/15/2024
cs.ROcs.AI

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Abstract

This paper presents the design and development of an innovative interactive robotic system to enhance audience engagement using character-like personas. Built upon the foundations of persona-driven dialog agents, this work extends the agent's application to the physical realm, employing robots to provide a more captivating and interactive experience. The proposed system, named the Masquerading Animated Social Kinematic (MASK), leverages an anthropomorphic robot which interacts with guests using non-verbal interactions, including facial expressions and gestures. A behavior generation system based upon a finite-state machine structure effectively conditions robotic behavior to convey distinct personas. The MASK framework integrates a perception engine, a behavior selection engine, and a comprehensive action library to enable real-time, dynamic interactions with minimal human intervention in behavior design. Throughout the user subject studies, we examined whether the users could recognize the intended character in both personality- and film-character-based persona conditions. We conclude by discussing the role of personas in interactive agents and the factors to consider for creating an engaging user experience.

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Cite this paper

@article{park2024towards,
  title  = {Towards Embedding Dynamic Personas in Interactive Robots: Masquerading Animated Social Kinematics (MASK)},
  author = {Jeongeun Park and Taemoon Jeong and Hyeonseong Kim and Taehyun Byun and Seungyoon Shin and Keunjun Choi and Jaewoon Kwon and Taeyoon Lee and Matthew Pan and Sungjoon Choi},
  year   = {2024},
  eprint = {2403.10041},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2403.10041v2}
}

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