Linna Zhang

Guizhou University, Shaanxi University of Technology

Papers

Total Citations

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About

Linna Zhang is a researcher at the forefront of 3D computer vision and intelligent robotic control. Her work primarily addresses two critical challenges: enabling machines to understand 3D point clouds without massive labeled datasets, and enhancing the precision of autonomous agricultural robots. Zhang’s most notable contribution is the development of **DCPoint**, a novel self-supervised learning framework that leverages a global-local dual contrast mechanism. This approach allows deep networks to learn powerful 3D representations from unlabeled data, directly tackling the data bottleneck that has long hindered progress in autonomous driving and robotics. With 8 citations since its 2024 publication, DCPoint is already recognized as a significant step forward in the field. Complementing this, Zhang has also advanced practical robotics by designing a **fast terminal sliding mode controller** for agricultural robots. By integrating an extended state observer with permanent magnet synchronous motor servo systems, her 2023 work dramatically improves path tracking accuracy, enabling robots to react swiftly to sudden terrain changes. This dual focus on foundational representation learning and applied control systems marks Zhang as a versatile engineer driving both the theory and real-world deployment of intelligent machines.