Baihan Chen
Papers
4
Total Citations
106
H-Index
3
About
Baihan Chen is a robotics researcher specializing in autonomous unmanned aerial vehicle (UAV) navigation, dynamic obstacle avoidance, and computer vision-based perception systems. His work addresses one of the most pressing challenges in autonomous robotics: enabling aerial robots to safely and efficiently operate in complex, dynamic environments. Chen's most significant contributions center on developing real-time frameworks that integrate vision-based sensing with intelligent trajectory planning. His gradient-based B-spline trajectory optimization approach, which has garnered over 40 citations since 2023, innovatively combines multiple map representations — geometric, occupancy, and ESDF — to generate collision-free paths around moving obstacles. Complementing this, his RGB-D camera-based dynamic obstacle tracking system (35 citations) advances the critical distinction between static and dynamic elements in 3D environments, a longstanding limitation of conventional voxel-based mapping methods. Perhaps most impressively, Chen has translated these algorithmic advances into real-world applications, developing an autonomous UAV inspection framework for hazardous tunnel construction sites (29 citations). This work demonstrates tangible impact in industrial safety and infrastructure assessment. With over 100 combined citations across just a few 2023 publications, Chen has rapidly established himself as a rising voice in autonomous aerial robotics research.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3
- 4