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About

Xiaoqun Tan is a robotics researcher whose work centers on advancing automated manufacturing and robotic locomotion. His primary contributions lie in developing intelligent systems for aircraft assembly, particularly through the design of multifunctional automatic drilling end effectors that integrate pressure units, drilling mechanisms, and control systems to reduce hole deviation. Tan has also pioneered vision-based detection methods, using line laser scanning and high-precision industrial cameras (e.g., Cognex Insight 5403) to locate base holes in large aviation parts and correct installation errors between workpieces and robotic drilling systems. His most cited papers—including "Design and Implementation of Multifunctional Automatic Drilling End Effector" (12 citations) and "Research on Edge Detection Algorithm Based on Line Laser Scanning" (11 citations)—demonstrate his impact on improving precision in aerospace manufacturing. Beyond assembly, Tan has explored quadruped robot locomotion, designing a composite rigid-flexible single leg for gallop gaits and hydraulically actuated systems for vertical hopping, as well as motion planning for wheeled robots in cluttered environments. His research bridges practical industrial automation with advanced robotics, offering solutions that enhance efficiency and accuracy in complex manufacturing tasks.