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About

Clark Youngdong Son is a leading researcher in multi-robot systems and safe autonomous navigation, with a focus on active sensing, environmental learning, and robust trajectory planning. His most impactful work, "Multi-Robot Active Sensing and Environmental Model Learning With Distributed Gaussian Process" (77 citations), pioneers a distributed framework for multiple robots to collaboratively explore unknown fields and locate global maxima using Gaussian process regression—a critical advance for environmental monitoring and search-and-rescue operations. Son also made significant contributions to safety-critical robotics with "Real-Time Robust Receding Horizon Planning Using Hamilton–Jacobi Reachability Analysis" (19 citations), which guarantees real-time safety under bounded disturbances, and "Fast Funnel Computation Using Multivariate Bernstein Polynomial" (10 citations), offering a tractable method for safety verification. His work on "Collision-Free Path Planning for Cooperative Aerial Manipulators" (9 citations) addresses complex constraints in aerial robotics, while "Fully Distributed Informative Planning for Environmental Learning" (7 citations) advances decentralized multi-robot coordination. With over 120 total citations, Son’s research bridges theoretical rigor and practical deployment, making him a key figure in autonomous systems.