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

This letter 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 (<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MASK</small>), 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 <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MASK</small> 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.

Authors

Institutions

Publication Details

Journal
IEEE Robotics and Automation Letters
Published
2024-08-22
DOI
https://doi.org/10.1109/lra.2024.3447470
Citations
3
Primary Topic
Persona Design and Applications
Type
article
Field-Weighted Citation Impact
1.12
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Jaewoon Kwon, Taemoon Jeong, Matthew Pan, Sungjoon Choi et al.
3 citations
IEEE Robotics and Automation Letters
Persona Design and Applications
1.12
article

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

Jaewoon Kwon, Taemoon Jeong, Matthew Pan, Sungjoon Choi, Taehyun Byun, Hyeonseong Kim, Keunjun Choi, Jeongeun Park, Taeyoon Lee, Seungyoun Shin
article en
3 citations

Abstract

This letter 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 (<sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MASK</small>), 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 <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">MASK</small> 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.

IEEE Robotics and Automation LettersVol. 9(10)
Korea University (KR), Queen's University (CA), Naver (South Korea) (KR)
Reduced inequalities
Openalex Percentile: Top 22%
Persona Design and Applications
1.12
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.