Keonyong Lee
Papers
2
Total Citations
22
H-Index
2
About
Keonyong Lee is a robotics researcher whose work bridges human-robot interaction and autonomous navigation. His primary research areas include humanoid path planning, simultaneous localization and mapping (SLAM), and human-robot interaction (HRI). Lee’s most notable contribution is his 2012 paper on humanoid path planning from an HRI perspective, which has garnered 17 citations. In this work, he introduced a scalable approach using waypoints with a time index, enabling humanoid robots to generate paths that feel natural from a human standpoint—a critical advancement for robots operating in human-centered environments. This method enhances both the robot’s efficiency and the user’s comfort during interaction. Additionally, Lee’s 2014 paper on EKF-based SLAM, with 5 citations, provides a rigorous analysis of how reference coordinate systems affect localization accuracy. By deriving EKF equations in the world coordinate system and comparing them with robot-centric frameworks, he clarified fundamental design choices that impact SLAM performance. Lee’s work demonstrates a commitment to making robots more intuitive and reliable in real-world settings, offering valuable insights for researchers developing autonomous systems that must coexist and collaborate with humans.
Research Focus
Key Achievements
Top Papers
- 1
- 2Analysis of the reference coordinate system used in the EKF-based SLAM5 citations · 2014