Xiaoyang Mao

Papers

Total Citations

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About

Xiaoyang Mao is a versatile researcher whose work spans agricultural technology and mobile robotics, with a focus on solving real-world problems through computational methods. In agricultural engineering, Mao developed a novel method for reconstructing 3D grape bunch models from 2D images, directly addressing the critical task of berry thinning in table grape production. This work, cited 8 times, enables farmers to automatically assess bunch compactness, form, and berry size—key factors determining market value—offering a practical tool for precision viticulture. In mobile robotics, Mao advanced gas distribution mapping (GDM) by introducing a propagated distance transform technique for structured indoor environments. This innovation, also with 8 citations, improves how mobile robots carrying gas sensors map volatile organic compounds, enhancing applications in environmental monitoring and safety. Mao’s contributions demonstrate a unique ability to bridge computer vision and robotic olfaction, with each paper laying groundwork for further innovation. Though early in citation impact, these works represent foundational steps in automating agricultural tasks and refining robotic sensing, highlighting Mao’s potential for significant future influence in both fields.