Yanjun Yu
Papers
1
Total Citations
2
H-Index
1
About
Driven by a passion for advancing assistive robotics, Yanjun Yu focuses on the control and automation of humanoid manipulators for healthcare applications. Their most-cited work, "Tracking control of humanoid manipulator using sliding mode with neural network and disturbance observer" (2025), introduces a robust control framework that integrates sliding mode control, neural networks, and disturbance observers to enhance precision and stability in nursing robots. This contribution is pivotal for enabling 6-degree-of-freedom (6-DOF) manipulators to perform complex, random daily care tasks—such as feeding or repositioning—for elderly and disabled individuals. With 2 citations already in its early publication, this paper signals growing recognition of Yu’s work in bridging theoretical control methods with real-world robotic assistance. By addressing challenges like external disturbances and model uncertainties, Yu’s research directly improves the safety and reliability of human-robot interaction in care settings. Their achievements underscore a commitment to developing intelligent, automated solutions that enhance quality of life, positioning them as a rising contributor to the fields of rehabilitation robotics and nonlinear control systems.
Research Focus
Key Achievements
Top Papers
- 1