James Ju Heon Lee

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About

James Ju Heon Lee is a leading researcher in autonomous marine robotics, specializing in motion planning and coordination under complex, dynamic ocean environments. His work addresses the critical challenge of navigating slow-moving robots through uncertain and time-varying currents, directly impacting marine science and environmental monitoring. Lee’s major contributions include pioneering a path planning framework that leverages ensemble forecasts—a technique from oceanography—to account for uncertain ocean currents, enabling more reliable and efficient robot navigation. He also developed a hierarchical planning approach for time-dependent flow fields, tackling the NP-hard problem of finding shortest paths in dynamic currents, which is essential for long-duration missions. With papers accumulating over 30 citations, his research demonstrates both theoretical depth and practical impact. Notably, Lee’s work on hierarchical Monte Carlo tree search (MCTS) for multi-vessel, multi-float systems introduces scalable coordination strategies for low-cost, underactuated floats paired with fully actuated surface vessels, promising cost-effective solutions for large-scale ocean sampling. His contributions are foundational for advancing autonomous systems in challenging marine settings.