Maohua Xiao

Papers

Total Citations

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About

Maohua Xiao is a pioneering researcher at the intersection of agricultural engineering and intelligent robotics, with a primary focus on developing automated solutions for modern farming challenges. His work centers on three key areas: deep learning-based identification systems, structural optimization of specialized robots, and precision path-tracking algorithms for agricultural automation. Xiao's most impactful contribution is his 2024 study on a deep learning-driven device for identifying and grasping dead broilers in flat houses, which has already garnered 11 citations for addressing critical welfare and efficiency issues in large-scale poultry farming. He further demonstrated his expertise in mechanical optimization through his work on pipe-climbing robots using ANSYS and MATLAB, achieving structural improvements validated by 3 citations. Most recently, in 2025, Xiao advanced greenhouse automation with an LQR-Pure Pursuit-based autonomous following robot, achieving high-precision path tracking in complex environments. His consistent use of sophisticated simulation tools like ANSYS Workbench and MATLAB underscores his commitment to rigorous, data-driven design. With a growing citation record and publications spanning 2022-2025, Xiao is establishing himself as a key innovator in agricultural robotics, bridging the gap between theoretical optimization and practical farm automation.