Papers
17
Total Citations
515
H-Index
10
About
Donghwa Lee is a robotics researcher whose work sits at the intersection of autonomous navigation, computer vision, and marine robotics. His most influential contributions focus on vision-based perception and localization for robotic systems operating in challenging environments, particularly underwater. His 2012 paper on vision-based object detection and tracking for autonomous underwater robots has garnered over 220 citations, establishing him as a leading voice in underwater robot navigation. Complementing this, his work on weighted template matching for AUV localization using artificial landmarks and his RGB-D sensor-based SLAM solution demonstrate a sustained commitment to advancing reliable robot positioning in difficult, sensor-degraded settings. Lee has also made meaningful contributions to hybrid SLAM approaches, combining 2D laser scanning with monocular camera imagery to address ambiguous environments such as long corridors. Perhaps his most distinctive line of work involves the development of JEROS — the Jellyfish Removal Robot System — an autonomous surface vehicle designed to combat jellyfish blooms threatening marine ecosystems and coastal industries, a project spanning multiple publications from 2012 to 2016. With a body of work accumulating hundreds of citations across underwater robotics, SLAM, and environmental applications, Lee's research reflects both technical rigor and real-world impact.
Research Focus
Key Achievements
Top Papers
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- 6AUV SLAM using forward/downward looking cameras and artificial landmarks20 citations · 2017
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- 9JEROS: Jellyfish Removal Robot System11 citations · 2012
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