Seungyoun Shin
Papers
2
Total Citations
5
H-Index
2
About
Seungyoun Shin is a robotics researcher whose work bridges the physical and social dimensions of human-robot interaction, with a particular focus on autonomous navigation and expressive robotic design. Shin’s research centers on two key areas: developing robust perception systems for mobile manipulators operating in constrained environments, and embedding dynamic, character-driven personas into interactive robots to enhance audience engagement. In their 2023 work on autonomous elevator boarding, Shin tackled the challenging problem of robust detection for mobile manipulators, demonstrating how robots can reliably navigate and board elevators in real-world settings—a critical capability for autonomous service robots operating in multi-story buildings. Their most notable contribution, the 2024 paper "Towards Embedding Dynamic Personas in Interactive Robots: Masquerading Animated Social Kinematic (MASK)," extends persona-driven dialog agents from the digital to the physical realm. This innovative system enables robots to adopt character-like personas, significantly enhancing audience engagement during interactions. Though early in their career, Shin’s work has already garnered attention, with these foundational papers accumulating citations that signal growing interest in their dual focus on robust autonomy and socially expressive robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2