Byung Moon Kim

Papers

Total Citations

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About

Byung Moon Kim is a robotics and control systems researcher whose work bridges foundational theory with practical validation. His most influential contribution centers on the stabilization and control of nonholonomic systems, particularly unicycle-type wheeled mobile robots. In his highly cited 2002 paper (91 citations), Kim provided a rigorous comparative study of multiple controllers for these systems, offering both theoretical analysis and—critically—experimental validation, a rarity at the time. This work remains a key reference for researchers tackling the challenges of underactuated, nonholonomic motion control. More recently, Kim has ventured into reinforcement learning, proposing a novel algorithm called Proximal Policy Gradient (PPG) in 2020. This method refines the relationship between vanilla policy gradient and PPO, aiming for improved stability and gradient alignment. While still early in its citation lifecycle, the work signals his expanding interest in learning-based control. Kim’s career exemplifies a commitment to both rigorous theory and real-world robot implementation, making his research valuable for students and engineers seeking to understand or deploy robust mobile robot controllers.