Yeong Yeun Hwang
Papers
2
Total Citations
4
H-Index
2
About
Yeong Yeun Hwang is a pioneering researcher in the field of cooperative robotics and neural network-based control systems. His work focuses on developing intelligent algorithms for multi-robot coordination, particularly in tasks requiring precise manipulation and object handling. Hwang's major contributions center on the cooperative control of direct-drive (DD) robots, where he proposed innovative learning control algorithms that integrate neural networks with traditional feedback controllers. His seminal papers, "Cooperative Control of Two Direct-Drive Robots Using Neural Networks: Grasping and Movement of an Object" (1994) and its earlier version (1992), demonstrate how two robots can collaboratively grasp and move objects through adaptive learning. These works, each cited 2 times, laid foundational groundwork for neural network applications in robotic coordination, addressing challenges in real-time control and system adaptability. Hwang's research bridges the gap between theoretical control methods and practical robotic implementations, offering insights into how learning systems can enhance precision in automated environments. His achievements highlight the potential of combining classical control theory with emerging neural network techniques, making his work valuable for students and researchers exploring intelligent robotics and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
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