Seung Hyeon Bang
Papers
7
Total Citations
100
H-Index
6
About
Seung Hyeon Bang is a leading researcher in humanoid robotics, specializing in locomotion planning, whole-body control, and learning-based manipulation. His work bridges the gap between theoretical control frameworks and real-world deployment on platforms like the DRACO 3 humanoid. Bang’s most impactful contribution is TRILL, a deep imitation learning framework for humanoid loco-manipulation (48 citations), which enables robots to learn complex tasks from human teleoperation demonstrations. He also developed TOWR+ and IHWBC for versatile locomotion planning and control (18 citations), and pioneered online gain adaptation for whole-body control under unknown disturbances (10 citations). His recent innovations include an RL-augmented MPC framework for agile bipedal footstep planning (7 citations) and a variable inertia MPC for fast maneuvers (2 citations). Bang’s work has been recognized for its practical impact on humanoid safety and agility, with his control methods enabling real-time dynamic obstacle avoidance and robust walking in human environments. His research is widely cited by robotics labs advancing bipedal locomotion and manipulation.
Research Focus
Key Achievements
Top Papers
- 1
- 2Versatile Locomotion Planning and Control for Humanoid Robots18 citations · 2021
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- 7Variable Inertia Model Predictive Control for Fast Bipedal Maneuvers2 citations · 2024