Papers
1
Total Citations
21
H-Index
1
About
Gunwoo Lee is a researcher at the forefront of mobile robotics and indoor positioning systems, with a focus on integrating sensor fusion technologies for autonomous navigation. His major contribution lies in developing methods that combine Simultaneous Localization and Mapping (SLAM) with Wi-Fi-based positioning, enabling mobile robots to collect data, localize themselves, and track movements more accurately in complex indoor environments. His most-cited work, "Fusion of the SLAM with Wi-Fi-Based Positioning Methods for Mobile Robot-Based Learning Data Collection, Localization, and Tracking in Indoor Spaces" (2020), has garnered 21 citations, reflecting its relevance to advancing robotic autonomy. Lee’s research addresses a critical challenge: while robots can navigate using maps, achieving rapid and precise self-localization remains difficult when relying solely on dead reckoning or environmental sensors. By fusing SLAM with Wi-Fi signals, his work enhances robustness in real-world settings like warehouses, offices, or hospitals. This achievement underscores his impact on practical robotic services, making his contributions valuable for students and researchers exploring sensor integration, autonomous systems, and indoor navigation technologies.
Research Focus
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Top Papers
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