Seungmoon Song
Papers
8
Total Citations
93
H-Index
6
About
Seungmoon Song is a leading researcher at the intersection of biomechanics and robotics, whose work bridges the gap between how humans walk and how robots should walk. His primary research areas include neuromuscular control of human locomotion, bipedal robot walking, and bio-inspired robotic design. Song’s major contributions lie in developing computational models that translate the neural and muscular dynamics of human walking into practical robotic controllers. His 2013 paper on integrating adaptive swing control into a neuromuscular human walking model (17 citations) laid the foundation for more robust, human-like gait generation. He has also explored the energetic cost of adaptive feet in walking (15 citations) and developed a bipedal robot that walks like an animation character (16 citations), showcasing his ability to merge engineering with creative design. Song’s work on regulating speed in neuromuscular running models (14 citations) and virtual neuromuscular control for bipedal robots (13 citations) further demonstrates his impact, with over 90 total citations across his most-cited works. His research has direct implications for humanoid robotics, prosthetics, and assistive devices, making him a key figure in advancing human-like locomotion in machines.
Research Focus
Key Achievements
Top Papers
- 1
- 2Development of a bipedal robot that walks like an animation character16 citations · 2015
- 3The energetic cost of adaptive feet in walking15 citations · 2011
- 4Regulating speed in a neuromuscular human running model14 citations · 2015
- 5Toward a virtual neuromuscular control for robust walking in bipedal robots13 citations · 2015
- 6
- 7Bayesian Optimization Using Domain Knowledge on the ATRIAS Biped4 citations · 2018
- 8