Papers
1
Total Citations
4
H-Index
1
About
Junjie Dai’s research focuses on advancing robotic manipulation through robust torque control and sensor integration, with a particular emphasis on flexible joint systems. His most-cited work, “Integrated Dual Torque Sensors and DOB of Robust Torque Control for Flexible Joint” (2025, 4 citations), tackles a critical challenge in interactive robotics: maintaining stability and precision in manipulators despite external disturbances. By proposing a dual torque sensor architecture combined with a disturbance observer (DOB), Dai’s contribution enhances the reliability of torque control in flexible joints—key components for safe human-robot interaction and delicate assembly tasks. This work addresses the inherent susceptibility of such systems to noise and dynamic uncertainties, offering a practical pathway toward more resilient robotic hardware. While still early in his career, Dai’s focus on sensor fusion and control theory positions him at the intersection of mechatronics and automation. His research holds promise for applications in collaborative robotics, where precise force modulation is essential. As his citation record grows, Dai’s work is likely to influence both academic studies and industrial designs for next-generation flexible manipulators.
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Top Papers
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