Dongmei Guo

Anhui University of Science and Technology

Papers

Total Citations

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About

Dongmei Guo is a pioneering researcher at the intersection of robotics and traditional Chinese art, whose work is redefining how machines replicate the nuanced beauty of Chinese calligraphy. Her primary research focuses on robotic stroke generation, brush trajectory extraction, and the development of hybrid models that blend physical brush dynamics with data-driven learning. Guo’s major contributions include the introduction of the composite-curve-dilation brush stroke model (CCD-BSM), which provides a robust framework for robotic arms to mimic the subtle pressure and curvature of human brushwork. Her 2022 paper on this model, along with its 2023 extension (CCD-BSMG), has garnered over 17 citations collectively, establishing her as a key figure in this niche field. Notably, her work on the footprint model for brush trajectory extraction offers a novel approach to capturing the essence of each stroke, bridging the gap between end-to-end learning and physical simulation. By collecting and analyzing thousands of brush strokes via robotic arms, Guo is paving the way for more expressive and culturally authentic robotic calligraphy, making her research essential for students and engineers interested in the fusion of art, robotics, and machine learning.