Zequn Tan
Papers
2
Total Citations
122
H-Index
2
About
Zequn Tan is a leading researcher in the integration of visible light positioning (VLP) and robotics, with a primary focus on achieving high-accuracy indoor localization for mobile robots. His most influential work, "High-Accuracy Robot Indoor Localization Scheme Based on Robot Operating System Using Visible Light Positioning" (2020), has garnered 120 citations, establishing him as a key figure in this niche. Tan’s major contribution lies in demonstrating that VLP—a cost-effective alternative to traditional radio-frequency systems—can deliver the precision required for robots operating in complex indoor environments, from industrial floors to public transit hubs. He further advanced the field by designing a novel VLC localization and navigation package for the Robot Operating System (ROS), bridging the gap between communication-based positioning and practical robotic autonomy. While his second paper on this topic has fewer citations, it showcases his iterative engineering approach, refining ROS-based frameworks for real-world deployment. Tan’s work is particularly notable for its applied impact, offering a scalable, low-cost solution that addresses the growing demand for service robots in GPS-denied spaces. His research continues to inspire new directions in sensor fusion and smart lighting systems for autonomous navigation.
Research Focus
Key Achievements
Top Papers
- 1
- 2