Papers

12

Total Citations

153

H-Index

7

About

Seokmin Hong is a robotics researcher whose work has made meaningful contributions to humanoid robot locomotion, motion control, and energy systems. His research centers on walking pattern generation, balance control, and teleoperation frameworks for bipedal humanoid robots, with a particular focus on the linear inverted pendulum model (LIPM) and zero moment point (ZMP) methodologies. Hong's most influential contribution — his 2013 paper on combining feedback and feedforward controllers for real-time walking pattern generation — has garnered 38 citations and addressed critical instabilities inherent in conventional LIPM-based approaches. Complementing this, his 2009 work on IMU-based walking motion imitation, allowing humanoid robots to replicate human locomotion in real time, has attracted 37 citations and demonstrated practical advances in teleoperation. Beyond locomotion control, Hong extended his expertise into energy sustainability with a 2016 study on piezoelectric energy harvesting from a humanoid robot's knee motion, reflecting an innovative interdisciplinary perspective. Across his portfolio, Hong has consistently tackled the dual challenges of stability and real-world applicability in humanoid robotics, producing a body of work that continues to inform researchers designing more capable and autonomous robotic systems.

Research Focus

Key Achievements

7
H-Index
12
Papers
153
Total Citations
13
Avg Citations/Paper
🏆 Most Cited Paper
Real-Time Walking Pattern Generation Method for Humanoid Robots by Combining Feedback and Feedforward Controller
38 citations · 2013
📈 Most Prolific Year: 2009 (4 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Korea University of Science and Technology, Korea Institute of Science and Technology, Korea University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
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