Papers
6
Total Citations
165
H-Index
6
About
Joo-Wan Kim is a pioneering roboticist whose research focuses on enabling robust perception and navigation for autonomous systems in extreme and challenging environments. His work spans three critical areas: all-weather motion estimation, illumination-resilient visual navigation, and maritime autonomy. Kim’s most impactful contribution is his development of a 3D ego-motion estimation system using low-cost mmWave radars, which overcomes the failure of conventional camera and LiDAR methods in fog, smoke, and other degraded visual conditions—a breakthrough cited 61 times. He has also revolutionized camera control for vision-based robotics, introducing Bayesian optimization techniques to proactively adjust camera attributes and exposure settings, thereby ensuring reliable visual navigation under dynamic lighting (over 66 combined citations). His notable achievements include the creation of the PoLaRIS Dataset for maritime object detection and tracking in challenging canal environments, and pioneering work on SLAM for water pipe rehabilitation robots. With over 165 total citations, Kim’s research is essential reading for anyone working on autonomous systems that must operate reliably when traditional sensors fail.
Research Focus
Key Achievements
Top Papers
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- 4Development of a side scan sonar module for the underwater simulator21 citations · 2017
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