Papers
19
Total Citations
478
H-Index
11
About
Woongyong Lee is a robotics and control systems researcher whose work sits at the intersection of human-robot interaction, advanced actuator control, and intelligent safety systems. His research spans collaborative robotics, exoskeleton control, hydraulic actuation, and impedance-based control frameworks — areas that are increasingly critical as robots move from isolated industrial environments into close proximity with humans. Lee's most influential contribution, "Collision Detection for Industrial Collaborative Robots: A Deep Learning Approach" (2019), has garnered 180 citations, reflecting the growing urgency of safe human-robot coexistence in manufacturing. His work on passivity-based admittance control for upper-limb exoskeletons (47 citations) demonstrates a strong command of physically grounded, mathematically rigorous control theory applied to assistive robotics. Equally notable are his contributions to electrohydrostatic and electro-hydraulic actuator compliance control, where he has developed disturbance observer frameworks that push the performance boundaries of hydraulic robotic systems. Across his portfolio, Lee consistently bridges theoretical rigor — drawing on passivity theory, sliding-mode control, and nonlinear dynamics — with real-world applicability. His work on friction modeling, programming by demonstration, and kinematic singularity avoidance further illustrates his breadth. For researchers entering robotics and control, Lee's body of work offers both foundational methods and cutting-edge solutions to some of the field's most pressing challenges.
Research Focus
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