Ping Bai
Papers
2
Total Citations
35
H-Index
2
About
Ping Bai’s research lies at the intersection of robotics, neural network control, and rehabilitation engineering, with a focus on developing intelligent systems that enhance human-robot interaction. Her most influential work, “Bilateral assessment of functional tasks for robot-assisted therapy applications” (2011), has garnered 29 citations and addresses a critical challenge in rehabilitation robotics: how to objectively evaluate a patient’s functional performance during therapy. This contribution has helped lay the groundwork for more adaptive, patient-centered robotic therapy. Earlier, Bai proposed a novel controller design for robot manipulators in “Robust Neural-Network Compensating Control for Robot Manipulator Based on Computed Torque Control” (2001, 6 citations). This work introduced a Functional Link Neural Network compensator within a computed torque control framework, effectively handling system uncertainties and improving trajectory tracking accuracy. By combining robust control theory with neural network adaptability, Bai’s research offers practical solutions for both industrial and therapeutic robotic applications. Her work continues to influence researchers developing smarter, safer, and more responsive robotic systems for real-world tasks.
Research Focus
Key Achievements
Top Papers
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