Yong Seon Moon

Papers

Total Citations

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About

Yong Seon Moon is a leading researcher in autonomous robotics, with a primary focus on underwater and indoor mobile robot navigation and localization. His most cited work introduces a particle filter approach for underwater robot localization using time difference of arrival (TDOA) of acoustic signals, achieving 21 citations. This research provides critical experimental analysis, demonstrating how the performance of the localization method depends on the degree of uncertainty in the system—a key insight for robust underwater operations. Moon also made significant contributions to indoor mobile robotics, implementing a complete autonomous navigation system that integrates map building, path planning, localization, local path planning, obstacle avoidance, and path tracking. Notably, he employed the Iterative Closest Point (ICP) algorithm to build grid-based maps from laser scan data, enabling reliable indoor navigation. His work bridges theoretical algorithms with practical implementation, offering valuable frameworks for researchers and engineers developing autonomous systems in challenging environments. With a career dedicated to advancing robot autonomy, Moon’s contributions continue to influence the fields of underwater robotics and indoor mobile navigation.