Yixuan Fan

Tsinghua University, Xinjiang University

Papers

Total Citations

H-Index

About

Yixuan Fan is a robotics and computer vision researcher whose work bridges natural language understanding, dexterous manipulation, and agricultural automation. His most impactful contribution is **VL-Grasp**, a 6-DOF interactive grasp policy that enables robots to identify and grasp objects in cluttered scenes based on human language directives—a critical step toward intuitive human-robot collaboration. This work, published in 2023, has already garnered **34 citations**, reflecting its timely relevance to the growing field of vision-and-language robotics. In parallel, Fan has advanced precision agriculture by developing a **marigold corolla detection model** based on an improved lightweight YOLOv7 architecture, achieving 13 citations for its 2024 iteration. This model addresses the pressing need for mechanized harvesting of marigold, a medicinal herb vital for liver protection and eye health, by enabling accurate, real-time flower detection in complex field conditions. Fan’s research uniquely spans from foundational robotic grasping challenges to applied agricultural solutions, demonstrating versatility and practical impact. His work not only pushes the boundaries of interactive robot manipulation but also contributes to sustainable farming technologies, making him a promising voice in embodied AI and agricultural robotics.