Min‐Gu Lee

About

Min-Gu Lee is a robotics researcher whose work spans human-robot interaction, field robotics, and autonomous navigation systems. His research addresses critical challenges in both educational robotics and practical reconnaissance applications, demonstrating a versatile approach to robotic system design. Lee’s most cited work, "The Interaction Design of Teaching Assistant Robots Based on Reinforcement Theory" (2006, 7 citations), explores how reinforcement learning principles can be applied to robot-mediated education, measuring task performance and reaction rates to optimize student-robot interactions. This foundational study bridges psychological theory with robotic implementation. In field robotics, Lee contributed to the development of modular robots capable of tree climbing and terrain navigation, as well as small-sized launchable reconnaissance robots designed for hazardous environments like military operations and disaster response. His technical contributions include the development of the KIDAR-B25, a compact 3D LIDAR system using optically coupled horizontal and vertical scanning mechanisms for autonomous navigation. Though his citation counts are modest, Lee’s work represents important early steps in integrating reinforcement theory with educational robotics and advancing compact sensing solutions for autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   The Interaction Design of Teaching Assistant Robots Based on Reinforcement Theory: With an Emphasis on the Measurement of Task Performance and Reaction Rate

   7 citations · 2006
2. 2
   Modular Type Robot for Field Moving and Tree Climbing

   3 citations · 2012
3. 3
   The Development of Small-sized Launchable Robot for Reconnaissance

   3 citations · 2012
4. 4
   Compact 3D lidar based on optically coupled horizontal and vertical scanning mechanism for the autonomous navigation of robots

   3 citations · 2011

Key Collaborators

Contact & Links