Yufan Cui
Papers
1
Total Citations
3
H-Index
1
About
Yufan Cui’s research centers on mobile robotics, simultaneous localization and mapping (SLAM), and the integration of open-source frameworks like ROS (Robot Operating System) for real-world autonomous navigation. In their most cited work, “Simulation and Implementation of SLAM Drawing Based on ROS Wheeled Mobile Robot” (2021), Cui demonstrated a practical pipeline for building a wheeled mobile robot using LiDAR and Raspberry Pi hardware, constructing a URDF model in ROS to enable real-time map generation of unknown indoor environments. This work bridges simulation and physical deployment, offering a replicable methodology for low-cost SLAM implementation—a critical step for advancing accessible robotics research. With 3 citations, the paper has informed subsequent studies in educational robotics and indoor mapping. Cui’s contributions highlight the growing importance of modular, hardware-agnostic approaches to autonomous navigation, and their work serves as a valuable resource for students and researchers seeking to prototype SLAM systems without expensive proprietary equipment. By combining theoretical modeling with hands-on implementation, Cui exemplifies the engineer-scientist approach that drives innovation in field robotics.
Research Focus
Key Achievements
Top Papers
- 1