Xin Dai
Papers
7
Total Citations
213
H-Index
6
About
Xin Dai is a leading researcher in wireless power transfer (WPT) and robotic manipulation, with a focus on advancing intelligent automation systems. His work centers on two key areas: adaptive control for cooperative robots and innovative WPT solutions for industrial and inspection robots. Dai’s major contributions include developing adaptive hybrid impedance control for dual-arm cooperative manipulation, which addresses object uncertainties and enhances robotic precision in complex tasks. In WPT, he has pioneered methods to improve power transfer capability and misalignment tolerance, such as energy injection techniques for bidirectional systems with multiple pickups and dual-coupled compensation topologies for substation inspection robots. His research on parameter estimation without communication has enabled efficient wireless charging for inspection robots, eliminating the need for additional channels. With over 200 citations across his most-cited papers, Dai’s work has significant impact, particularly his 2022 paper on adaptive impedance control (77 citations) and his 2020 study on energy injection for WPT (44 citations). Notable achievements include designing coupling mechanisms with multidegree freedom for multistage WPT systems and phase-shifted control using dual excitation units, showcasing his ability to solve real-world challenges in robotics and power transfer.
Research Focus
Key Achievements
Top Papers
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