Papers
14
Total Citations
412
H-Index
8
About
Jonghoon Park is a robotics researcher whose career spans over two decades of foundational and applied contributions to robot control, human-robot interaction, and humanoid systems. His work addresses some of the most challenging problems in modern robotics, ranging from industrial manipulator control to bipedal locomotion and collaborative robot safety. Park's most cited work, "Collision Detection for Industrial Collaborative Robots: A Deep Learning Approach" (2019, 180 citations), demonstrates his ability to bridge classical control theory with modern machine learning, providing a reliable safety framework critical for human-robot collaboration in industrial environments. His 2007 paper on General ZMP Preview Control (77 citations) represents a significant advancement in bipedal walking, extending conventional methods to full dynamics modeling for more realistic humanoid locomotion. Earlier contributions, including robust H∞ PID control for industrial manipulators (1999, 48 citations), established his expertise in disturbance-resilient motion control. Park's research portfolio also encompasses kinematic singularity handling, Lie group-based tracking, redundancy resolution, and friction modeling for collaborative robots. His most recent work on soft wearable robotic suits signals a growing interest in assistive technologies. Collectively, his publications reflect a researcher deeply committed to making robots safer, smarter, and more capable across both industrial and human-centered domains.
Research Focus
Key Achievements
Top Papers
- 1
- 2General ZMP Preview Control for Bipedal Walking77 citations · 2007
- 3Design of a Robust H∞ PID Control for Industrial Manipulators48 citations · 1999
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- 7Multiple tasks manipulation for a robotic manipulator16 citations · 2004
- 8Tracking on lie group for robot manipulators13 citations · 2014
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