Shoulong Xu
Papers
3
Total Citations
30
H-Index
3
About
Shoulong Xu is a pioneering researcher at the intersection of robotics, intelligent control, and nuclear engineering. His work focuses on two critical, high-stakes domains: developing advanced control systems for collaborative robots and ensuring the resilience of robotic systems in extreme radiation environments. Xu’s most impactful contribution is his "Vision-admittance-based adaptive RBFNN control with a SMC robust compensator," a sophisticated framework that integrates neural network adaptation with sliding mode control to enhance the precision and safety of collaborative parallel robots. This work, his most cited with 22 citations, addresses fundamental challenges in human-robot interaction. In parallel, Xu has made significant strides in nuclear robotics. He demonstrated the novel use of a monolithic active pixel sensor (MAPS) camera for low-dose-rate gamma-ray detection without conversion layers, a breakthrough for remote sensing in hazardous zones. His 2024 study on radiation damage systematically evaluates the vulnerability of control and sensing electronics, proposing targeted shielding solutions. By bridging adaptive control theory with the practical demands of nuclear decommissioning and inspection, Xu is charting a vital path for robots to operate reliably where humans cannot.
Research Focus
Key Achievements
Top Papers
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