Ye Bai
Papers
2
Total Citations
12
H-Index
2
About
Ye Bai is a rising researcher in robotics and intelligent manufacturing, whose work bridges the gap between traditional kinematic algorithms and modern machine learning. His key research areas include inverse kinematics, robot manipulator control, and programming by demonstration for precision assembly. Bai's most influential contribution is a hybrid method that combines the FABRIK algorithm with a custom artificial neural network to solve inverse kinematics for generic serial robot manipulators—a paper that has already garnered 9 citations since its 2024 publication. This approach offers a more flexible and accurate alternative to conventional solvers, with significant implications for industrial automation. Additionally, his 2023 work on machine learning models for precise assembly using programming by demonstration (3 citations) demonstrates his commitment to making robotic systems more intuitive and adaptable. By integrating data-driven techniques with classical robotics, Bai is helping to pave the way for smarter, more efficient manufacturing processes. His early citation impact signals a promising trajectory in the field.
Research Focus
Key Achievements
Top Papers
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- 2