Young-Hwan Oh
Papers
2
Total Citations
8
H-Index
2
About
Young-Hwan Oh is a researcher dedicated to advancing biologically inspired control systems for robotic manipulation. His primary research areas encompass neural oscillator-based control, bio-inspired algorithms, and the unified motion control of whole robotic arm-hand systems. Oh’s major contribution lies in developing control frameworks that emulate the natural, rhythmic movements observed in humans and animals, enabling robots to perform complex tasks without explicit computation. His 2014 work on a biologically inspired control algorithm for whole robotic arm-hand motion (5 citations) demonstrates how these approaches can efficiently solve control problems for multi-degree-of-freedom systems. Earlier, his 2009 paper on self-adapting robot arm movement employing neural oscillators (3 citations) established a foundation for using neural oscillators to generate robust, rhythmically dynamic movements that adapt to changing task environments. Though his citation counts are modest, Oh’s work is notable for its pioneering integration of neural entrainment principles into robotic control, offering a pathway toward more fluid, human-like robot motion. His research holds significant promise for applications in prosthetics, assistive robotics, and industrial automation, where adaptive, natural movement is critical.
Research Focus
Key Achievements
Top Papers
- 1
- 2Self-adapting robot arm movement employing neural oscillators3 citations · 2009