Papers
13
Total Citations
692
H-Index
9
About
Gim Hee Lee is a prominent researcher in robotics, computer vision, and autonomous systems, with particular expertise in simultaneous localization and mapping (SLAM), visual pose estimation, and micro aerial vehicles (MAVs). His work has significantly advanced the capability of robots to navigate, map, and operate autonomously in GPS-denied and dynamically changing environments. Lee's most influential contribution, "Vision-Controlled Micro Flying Robots" (2014), has accumulated nearly 300 citations and remains a landmark reference for autonomous microhelicopter design and navigation. His robust pose-graph SLAM framework, which elegantly applies Expectation-Maximization to handle erroneous loop closures, further demonstrates his methodological rigor in tackling fundamental robotics challenges. His research on multi-camera self-calibration for MAVs reflects a consistent drive to push the boundaries of aerial robot perception. More recently, Lee has expanded into deep learning-driven 6D object pose estimation and lifelong mapping in changing environments, addressing critical needs in robotic manipulation and long-term autonomy. His involvement in the EU-funded SFly swarm robotics project and practical applications in automated offshore welding underscore the real-world relevance of his research. With hundreds of citations across diverse domains, Lee's work continues to shape modern robotics and computer vision research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Robust pose-graph loop-closures with expectation-maximization84 citations · 2013
- 3
- 4Robust 6D Object Pose Estimation by Learning RGB-D Features51 citations · 2020
- 5
- 6A benchmarking tool for MAV visual pose estimation44 citations · 2010
- 7SFly: Swarm of micro flying robots36 citations · 2012
- 8Object detection and motion planning for automated welding of tubular joints23 citations · 2016
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