Jiun Fatt Chow
Papers
1
Total Citations
7
H-Index
1
About
Jiun Fatt Chow is a robotics researcher specializing in autonomous navigation for unmanned aerial vehicles (UAVs) in GPS-denied environments. His work centers on developing robust localization and odometry systems, particularly through LiDAR-inertial sensor fusion, enabling aerial robots to operate reliably in challenging underground or indoor settings. His most-cited paper, "Toward Underground Localization: Lidar Inertial Odometry Enabled Aerial Robot Navigation" (2019, 7 citations), presents a laser-based localization method that overcomes the limitations of GPS, WiFi, and camera-based approaches in deep subterranean spaces. This contribution is critical for applications in mining, search-and-rescue, and infrastructure inspection, where traditional positioning fails. Chow’s research advances the state of the art in real-time, drift-reduced state estimation, demonstrating how aerial robots can navigate with precision in dark, unstructured, and feature-sparse environments. His work has been recognized for its practical impact on field robotics, bridging the gap between laboratory algorithms and real-world deployment. By tackling the fundamental challenge of localization without external references, Chow is helping to unlock the full potential of autonomous UAVs in some of the most demanding operational contexts.
Research Focus
Key Achievements
Top Papers
- 1