Jun won Lee

Korea Institute of Science and Technology, Korea Environmental Industry and Technology Institute

Papers

Total Citations

H-Index

About

Jun Won Lee is a robotics researcher whose work centers on humanoid robot manipulation and human-like motion generation. His primary contributions lie in developing control frameworks that enable humanoid robots to interact with objects and environments in ways that mirror human capabilities. Notably, his 2012 paper on "Humanoid's dual arm object manipulation based on virtual dynamics model" (11 citations) introduced an innovative approach for coordinating two arms to handle objects of varying shapes and sizes, addressing a critical challenge for robots operating in human-centered spaces. This work provided a foundation for more intuitive and adaptable manipulation strategies. Additionally, Lee explored machine learning applications in robotics through his research on "SVM-based system for point-to-point hand movement" (2 citations), which proposed a simpler, data-driven method for generating human-like arm trajectories, moving away from complex dynamical systems. While his citation counts reflect a focused, early-career impact, his research contributes to the broader goal of making humanoid robots practical assistants in daily life, emphasizing both theoretical modeling and real-world applicability in manipulation and motion planning.