Papers
4
Total Citations
14
H-Index
2
About
Xiayu Zhao is a rising leader in construction robotics, advancing the integration of adaptive intelligence and multi-robot systems for infrastructure inspection and human-robot collaboration. Her core research spans deep reinforcement learning, sensor fusion, and large language model (LLM) control, targeting the inefficiencies of pre-programmed robots in dynamic construction environments. In her most-cited work, "A computational method for real‐time roof defect segmentation in robotic inspection" (2025, 9 citations), she developed a real-time defect segmentation algorithm that enhances robotic inspection accuracy. She further pioneered a deep reinforcement learning-based cyber-physical system to optimize robot navigation efficiency, and designed a hierarchical aerial-ground multi-robot system combining hexacopter mapping with hexapod ground robots for balanced coverage and detail. Notably, Zhao is at the forefront of grounding LLMs in robot control, enabling intuitive human-robot collaboration that reduces complexity for construction workers. Her contributions are already shaping safer, more efficient construction sites, with her 2025 publications collectively garnering over 14 citations and establishing her as a key innovator in adaptive construction automation.
Research Focus
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Top Papers
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