Papers
1
Total Citations
5
H-Index
1
About
Guihua Han is a robotics researcher whose work focuses on the complex control challenges of legged locomotion, particularly for hydraulic quadruped robots. Her key research areas include multi-joint coordination, decoupling control, and neural network applications in robotic systems. Han’s most notable contribution is her pioneering work on PID neural network decoupling control, which addresses the critical problem of movement coupling among joints in hydraulic quadruped robots—a challenge inherent to redundant transmission systems. This research, published in 2019, has accumulated 5 citations and provides a foundational solution for achieving coordinated multi-degree-of-freedom movement in these advanced robots. By tackling the urgent need for effective decoupling strategies, Han’s work directly supports the development of more agile and stable legged robots, with potential applications in search-and-rescue, exploration, and industrial automation. Her contributions are particularly valuable for students and researchers interested in the intersection of neural network control and robotic locomotion, offering a practical approach to one of the field’s most persistent engineering hurdles.
Research Focus
Key Achievements
Top Papers
- 1