Yonghwan Oh
Papers
17
Total Citations
276
H-Index
8
About
Yonghwan Oh is a robotics researcher whose work has fundamentally advanced the science of humanoid robot locomotion and control. His primary contributions lie in walking pattern generation, center of mass (CoM) dynamics, and bipedal robot stability — areas that sit at the challenging intersection of control theory, kinematics, and biomechanics. Oh's most influential work, "Posture/Walking Control for Humanoid Robot Based on Kinematic Resolution of CoM Jacobian With Embedded Motion" (2007, 136 citations), established a landmark framework for generating stable walking patterns using simplified bipedal models combined with CoM Jacobian resolution — a method widely adopted by subsequent researchers. His complementary studies on feedforward-feedback control architectures and analytical CoM trajectory generation further refined real-time walking capabilities, addressing longstanding instabilities inherent in the linear inverted pendulum model. Beyond locomotion, Oh extended his work into biologically inspired neural oscillator control, energy-efficient parallel mechanism leg design, and networked humanoid systems, as exemplified by the MAHRU ubiquitous robotic companion platform. His research on closed-loop CoM estimation using force-torque sensors reflects a deep commitment to practical, deployable systems. With over 250 cumulative citations, Oh's body of work represents a meaningful and lasting contribution to the field of humanoid robotics.
Research Focus
Key Achievements
Top Papers
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- 4An Analytical Method to Generate Walking Pattern of Humanoid Robot14 citations · 2006
- 5Network-based Humanoid ‘MAHRU’ as Ubiquitous Robotic Companion10 citations · 2008
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- 10A walking pattern generation method of humanoid robot MAHRU-R7 citations · 2009