Papers
1
Total Citations
5
H-Index
1
About
Yongtai Ye is a robotics researcher whose work focuses on the control and coordination of complex robotic systems, particularly hydraulic quadruped robots. His key research areas include multi-joint decoupling control, neural network-based PID control, and the dynamics of redundant transmission systems. Ye’s major contribution lies in addressing the challenge of movement coupling among multiple degrees of freedom in hydraulic quadruped robots, where kinematic chains interact in complex ways. He proposed a PID neural network decoupling control method to achieve coordinated movement among joints, significantly improving stability and precision in these systems. His most cited paper, “Research on PID Neural Network Decoupling Control Among Joints of Hydraulic Quadruped Robot” (2019), has garnered 5 citations, reflecting its relevance in the field of advanced robotics control. Ye’s work is notable for bridging neural network techniques with traditional control theory, offering practical solutions for real-world robotic applications. His research continues to inspire further developments in legged robot locomotion and multi-joint coordination, making him a valuable contributor to the robotics community.
Research Focus
Key Achievements
Top Papers
- 1