Jiaxu Wang
Papers
5
Total Citations
57
H-Index
4
About
Jiaxu Wang is a robotics and control systems researcher whose work spans advanced motor control, mechanical transmission modeling, and emerging perception technologies for robotic applications. His research addresses some of the most pressing challenges in deploying robots in real-world, unstructured environments, with a particular emphasis on reliability, precision, and adaptability. Wang's most influential contributions include pioneering barrier Lyapunov function-based adaptive control for permanent magnet synchronous motors (PMSM), which enforces full-state and input constraints to enhance robot safety and performance — a paper that has attracted 21 citations since 2022. Complementing this, his highly cited work on harmonic drive modeling (20 citations) tackled the critical problem of transmission compliance and hysteresis degradation over service time, offering more accurate models to improve long-term robotic joint control. His research extends into space robotics, where he has analyzed and predicted transmission errors in harmonic reducers under varying load conditions, and into adaptive impedance control using fuzzy logic for nuanced human-robot interaction. More recently, Wang has ventured into event-based 3D reconstruction using neural radiance fields augmented with physical priors — demonstrating a broadening research vision toward next-generation robotic perception. Collectively, his work reflects a commitment to bridging theoretical control design with practical robotic deployment.
Research Focus
Key Achievements
Top Papers
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- 3Physical Priors Augmented Event-Based 3D Reconstruction9 citations · 2024
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