Lingxiu Zhang

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About

Lingxiu Zhang is a researcher at the forefront of construction robotics and intelligent automation, with a focus on integrating computer vision and machine learning into robotic systems for built environments. Her most-cited work, "Object Segmentation by Spraying Robot Based on Multi-Layer Perceptron" (2022), addresses a critical challenge in construction robotics: enabling robots to accurately perceive and segment objects in complex, unstructured job sites. By jointly analyzing the characteristics of the construction environment, object types, and robot structure, Zhang developed a vision-driven approach that allows spraying robots to identify both the type and spatial location of targets in real time. This contribution bridges the gap between theoretical perception models and practical robotic deployment, enhancing the autonomy and precision of on-site construction tasks. With growing citation impact, Zhang’s research is laying essential groundwork for safer, more efficient automated construction. Her work is particularly notable for its interdisciplinary synthesis of robotics, sensor fusion, and deep learning—offering a scalable solution for the next generation of intelligent construction machinery.