Heechan Shin

Korea Advanced Institute of Science and Technology

Papers

Total Citations

H-Index

About

Heechan Shin is a robotics researcher whose work spans autonomous navigation, human-robot interaction, and legged locomotion control. His research focuses on making robots more capable, comfortable, and intelligent in real-world environments — from indoor service settings to dynamic moving platforms. Shin's most recognized contribution is his optimization-based path planning framework for person-following robots, which addresses the critical challenge of maintaining target visibility in occluded indoor environments. This work has garnered 15 citations and represents a meaningful advance in socially assistive robotics. Complementing this, his kinodynamic comfort trajectory planning method for car-like robots — with 14 citations — introduced a principled framework for minimizing forces experienced by passengers and cargo, an increasingly relevant concern as autonomous personal mobility expands. Together, these two works establish Shin as a thoughtful researcher bridging technical rigor with human-centered design. More recently, Shin has extended his interests to quadruped robotics, developing a learning-based adaptive control system that enables four-legged robots to actively stabilize themselves on six-degree-of-freedom moving platforms such as buses and aircraft — a challenging and practically significant problem. Across his career, Shin exemplifies a researcher steadily pushing the boundaries of robot autonomy in complex, human-inhabited spaces.