Young-Ha Shin
Papers
4
Total Citations
210
H-Index
3
About
Young-Ha Shin is a leading roboticist whose work bridges the gap between theoretical control and real-world hardware design for legged locomotion. His primary research areas span model predictive control, mechanical design optimization, and actuator innovation for quadruped and humanoid robots. Shin’s most influential contribution is the development of a Representation-Free Model Predictive Control (RF-MPC) framework, which directly uses rotation matrices to control dynamic motions in quadrupeds—a breakthrough that has garnered 173 citations for liberating controllers from singularities and simplifying complex 3D maneuvers. He also led the design of KAIST HOUND, a quadruped platform optimized for fast, efficient locomotion; his mixed-integer nonlinear optimization of gear trains achieved a target speed of 3 m/s while minimizing energy cost, earning 30 citations. Further demonstrating his versatility, Shin invented the Dual Reduction Ratio Planetary Drive (DRPD), a compact actuator that switches between two gear ratios for articulated robots, and developed a real-time footstep planner for humanoids that incorporates foot angle differences into cost-to-go heuristics. His work is foundational for advancing agile, energy-efficient robots capable of navigating challenging terrains.
Research Focus
Key Achievements
Top Papers
- 1Representation-Free Model Predictive Control for Dynamic Motions in Quadrupeds173 citations · 2021
- 2
- 3
- 4