Yanxi Mao

Southern University of Science and Technology

Papers

Total Citations

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About

Yanxi Mao is a researcher at the forefront of intelligent robotics and smart manufacturing, with a focus on automating complex, high-risk industrial tasks. Their work bridges the gap between robotic systems and real-world manufacturing challenges, particularly in aerospace and industrial maintenance. Mao’s comprehensive survey on pole climbing robots (2022, 4 citations) established a foundational taxonomy of these machines, systematically analyzing their designs and applications to replace human workers in dangerous pole-climbing tasks—a critical contribution to industrial safety and automation. Building on this, Mao’s 2025 study on surface-roughness prediction for small-batch workpieces (3 citations) introduced the novel Response Surface Methodology-BP Neural Network (RSM-BPNN), a hybrid model that optimizes process parameters in aerospace robotic grinding. This work addresses a key gap in smart manufacturing by enabling accurate surface quality predictions across varying sample sizes and runtime conditions, directly enhancing precision and efficiency in high-stakes production. Though early in their career, Mao’s targeted contributions to robotic automation and adaptive manufacturing models signal a promising trajectory, with potential to shape safer, smarter industrial systems.