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About

PooGyeon Park is a leading researcher in robotics and control systems, with a primary focus on advanced motion control, trajectory generation, and embodied artificial intelligence. His most impactful work, "An Improved Adaptive Sliding Mode Control Based on Time-Delay Control for Robot Manipulators" (2022, 46 citations), introduces a novel adaptive sliding mode control (ASMC) scheme that compensates for time-delay estimation errors, significantly enhancing the precision and robustness of robot manipulators. This contribution addresses critical challenges in industrial automation and human-robot interaction. Park also pioneered "Jerk Limited Velocity Profile Generation for High Speed Industrial Robot Trajectories" (2005, 21 citations), a foundational method for generating smooth, high-speed trajectories that minimize mechanical stress and improve performance in manufacturing. More recently, his work on "Reinforced Intelligence Through Active Interaction in Real World: A Survey on Embodied AI" (2025, 6 citations) explores how robots can learn through active environmental interaction, bridging simulation and reality. Additionally, his research on underwater sound source localization using hydrophones demonstrates his versatility in sensor-based robotics. With over 75 citations across his key publications, Park’s work continues to influence both theoretical control design and practical robotic applications, making him a notable figure in modern robotics research.