Jimyeong Woo
Papers
1
Total Citations
8
H-Index
1
About
Jimyeong Woo is a robotics researcher whose work centers on autonomous navigation and perception in complex, real-world environments. His primary research areas include Simultaneous Localization and Mapping (SLAM), LIDAR-based sensing, and mobile robotics, with a particular focus on overcoming the challenges posed by dynamic, unpredictable settings. Woo’s most cited work, "Comparison and Analysis of LIDAR-based SLAM Frameworks in Dynamic Environments with Moving Objects" (2021, 8 citations), provides a rigorous evaluation of Hector SLAM, GMapping, and Karto SLAM under realistic conditions with moving obstacles. Through extensive mobile robot experiments, he systematically benchmarks these frameworks, offering critical insights into their robustness and limitations when faced with dynamic objects—a common but often overlooked challenge in real-world deployment. This comparative analysis serves as a valuable resource for researchers and practitioners selecting SLAM algorithms for applications ranging from warehouse logistics to autonomous driving. Woo’s contributions help bridge the gap between theoretical SLAM performance and practical, dynamic-environment operation, establishing him as a thoughtful voice in advancing reliable, real-time robotic perception.
Research Focus
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Top Papers
- 1