Yuhang Kang

Chinese Academy of Sciences

Papers

2

Total Citations

15

H-Index

2

About

Yuhang Kang is a researcher specializing in visual SLAM (Simultaneous Localization and Mapping) and visual place recognition for mobile robotics. His work addresses a critical challenge in autonomous navigation: enabling robots to operate reliably in dynamic, real-world environments where traditional SLAM algorithms fail due to moving objects. Kang’s major contributions include the development of DFPC-SLAM, a stereo vision-based method that leverages semantic information to classify feature points as dynamic or static, dramatically improving localization accuracy in cluttered scenes. He has also advanced visual place recognition through a novel distilled representation approach that employs patch-based local-to-global similarity strategies, achieving robust performance with compact feature descriptors. His most-cited paper (12 citations) on this topic demonstrates growing influence in the field. By tackling the fundamental tension between static assumptions and dynamic realities, Kang’s work is paving the way for more resilient autonomous systems in applications ranging from service robotics to autonomous driving.

Research Focus

Key Achievements

2
H-Index
2
Papers
15
Total Citations
8
Avg Citations/Paper
🏆 Most Cited Paper
Distilled representation using patch-based local-to-global similarity strategy for visual place recognition
12 citations · 2023
📈 Most Prolific Year: 2023 (2 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Chinese Academy of Sciences

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago