Rui Nan

Papers

Total Citations

H-Index

About

Rui Nan is a researcher whose work sits at the intersection of robotics, machine vision, and intelligent manufacturing. Their primary research areas include vision-guided robotic systems, automated grinding and finishing, and robotic grasping in complex environments. Nan’s major contributions center on integrating visual perception with robotic manipulation to enhance precision and flexibility in industrial applications. Notably, their work on vision-guided grinding robots for metal surface edge finishing and wheel hub casting processing has demonstrated how deep learning and computer vision can enable robots to autonomously locate, assess, and execute grinding tasks—effectively giving machines “eyes” to guide their actions. Their most cited papers, including “Vision-guided robot application for metal surface edge grinding” and “Application Research of Vision-Guided Grinding Robot for Wheel Hub Castings,” each with 5 citations, reflect growing interest in this practical, industry-driven approach. Nan has also advanced robotic grasping technology by developing a lightweight model that integrates large kernel convolutions and residual connections, enabling real-time, high-performance grasping from RGB and depth images. This work addresses the critical need for efficient, adaptable robotic systems in dynamic environments. For students and researchers exploring the future of smart manufacturing, Rui Nan’s research offers a compelling blueprint for how vision and robotics can work in concert to automate complex, precision-demanding tasks.