Xinyu Hu
Papers
2
Total Citations
8
H-Index
2
About
Xinyu Hu is a robotics researcher whose work focuses on intelligent perception and precision agriculture, with a particular emphasis on autonomous navigation and non-chemical weed control. Her key research areas include computer vision for robotic systems, structural constraint-based obstacle detection, and laser-targeting technologies for sustainable farming. Hu’s most cited paper, "Transmission Line Obstacle Detection Based on Structural Constraint and Feature Fusion" (2020, 5 citations), introduces a novel method for patrol robots to accurately detect obstacles using symmetrically mounted cameras and feature fusion, directly contributing to safer autonomous navigation in complex environments. More recently, her 2025 paper "Progress and Challenges in Research on Key Technologies for Laser Weed Control Robot-to-Target System" (3 citations) addresses the growing demand for precision agriculture by analyzing the core technologies—target identification, tracking, and laser delivery—that enable highly selective, chemical-free weed management. Though her citation counts are modest, Hu’s work is notable for bridging practical robotic challenges with emerging agricultural needs, positioning her as a contributor to the future of autonomous field robotics and environmentally sustainable farming technologies.
Research Focus
Key Achievements
Top Papers
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- 2