Kun Wan

Yunnan Normal University

Papers

1

Total Citations

2

H-Index

1

About

Dr. Kun Wan is a leading researcher in autonomous driving and intelligent robotics, with a primary focus on advancing visual simultaneous localization and mapping (SLAM) technologies. Their most notable contribution is the development of SPVL-vSLAM, a novel visual SLAM system designed specifically for semi-static environments—a critical challenge in autonomous navigation. This work introduces Semantic Patch-NetVLAD loop closure detection, which robustly handles both short-term dynamic obstacles and long-term environmental changes that traditionally degrade SLAM performance. With over 2 citations on this recent 2025 publication, Dr. Wan’s research addresses a fundamental gap in autonomous driving technology, where existing SLAM systems often fail in real-world, ever-changing scenes. By integrating semantic understanding with visual localization, their work enhances the reliability and accuracy of autonomous vehicle positioning. Dr. Wan’s contributions are particularly significant for the development of safer, more adaptive self-driving systems, positioning them as an emerging expert in the intersection of computer vision, robotics, and intelligent transportation. Their research continues to push the boundaries of how autonomous systems perceive and navigate complex, dynamic environments.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
SPVL-vSLAM: Visual SLAM for Autonomous Driving Vehicles Based on Semantic Patch-NetVLAD Loop Closure Detection in Semi-Static Scenes
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 1
🏛 Institutions: Yunnan Normal University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago