Loi Huynh
Papers
1
Total Citations
6
H-Index
1
About
Loi Huynh is a researcher whose work sits at the intersection of haptics, human-robot interaction, and shared control systems. His most-cited paper, "A novel MPC approach to optimize force feedback for human-robot shared control" (2015, 6 citations), tackles a fundamental challenge in the field: rendering stable and intuitive force feedback in the presence of unpredictable human behavior. Huynh identified that standard adaptive and optimal control methods often fail when applied to many commercial haptic devices, which lack the necessary state-space models. To address this, he introduced a novel Model Predictive Control (MPC) framework specifically designed to optimize force feedback in real time, accounting for human uncertainty without requiring a full device model. This work provides a practical, robust solution for improving the transparency and safety of shared-control systems, from surgical robots to teleoperation. While his citation count reflects a focused, emerging impact, Huynh’s contribution is notable for bridging a critical gap between control theory and real-world haptic hardware, offering a pathway for more reliable human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1