Young mok Yun
Papers
1
Total Citations
2
H-Index
1
About
Young Mok Yun is a robotics researcher whose work centers on humanoid robot motion planning and human-robot interaction, with a particular focus on generating natural, human-like arm movements. His key contribution lies in simplifying complex dynamical systems for robot trajectory generation, as demonstrated in his 2012 paper on an SVM-based system for point-to-point hand movement. This work introduced a more accessible approach to creating human-like trajectories for humanoid robot arms, moving away from the traditionally complex dynamical models that had dominated the field for over a decade. While his most-cited paper has accumulated 2 citations, reflecting the specialized nature of early-stage robotics research, Yun’s work contributes to the broader goal of making robots move more intuitively and interact more seamlessly with humans. His research bridges machine learning and robotics, offering practical solutions for improving robot dexterity and motion naturalness. For students and researchers exploring humanoid robotics, Yun’s approach represents a step toward more efficient and human-friendly robotic systems.
Research Focus
Key Achievements
Top Papers
- 1SVM-based system for point-to-point hand movement2 citations · 2012