Juhan Yoo
Papers
1
Total Citations
3
H-Index
1
About
Juhan Yoo is a researcher advancing the field of autonomous airport ground operations, with a primary focus on real-time 3D perception and semantic segmentation for aviation infrastructure. His most notable contribution is the development of a real-time semantic segmentation system for 3D LiDAR point clouds, specifically designed for aircraft engine detection in autonomous jetbridge operations. This work, published in 2024 and already garnering 3 citations, addresses a critical safety and efficiency challenge in automated aircraft docking, where precise identification of engine position is essential to prevent collisions. By leveraging spinning 3D LiDAR sensors, Yoo’s approach enables robust, real-time object recognition in complex airport environments, bridging the gap between computer vision and practical aviation automation. His research demonstrates a clear pathway toward fully autonomous jetbridge systems, reducing human error and turnaround times. Yoo’s work sits at the intersection of robotics, sensor fusion, and transportation safety, offering a scalable solution for next-generation smart airports.
Research Focus
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Top Papers
- 1