Kyung-Sik Park
Papers
2
Total Citations
97
H-Index
2
About
Dr. Kyung-Sik Park is a leading researcher in autonomous robot navigation, with a focus on integrating deep reinforcement learning (DRL) to enable mobile robots to operate safely and efficiently in complex, crowded environments. His most cited work (76 citations) addresses a critical real-world constraint—limited sensor field of view—by developing DRL-based navigation strategies that allow robots to plan paths and avoid obstacles even with restricted perception. This breakthrough is foundational for deploying service robots in human-centric spaces. Dr. Park further advances the field by tackling the challenge of human-robot interaction, demonstrating how DRL navigation policies can be rapidly adapted to align with individual human preferences for speed, proximity, and social norms (21 citations). His research bridges the gap between theoretical DRL algorithms and practical, user-friendly robotic systems. By focusing on adaptability and real-world constraints, Dr. Park’s contributions are shaping the next generation of autonomous robots that can seamlessly integrate into daily life, with his work cited by researchers in robotics, AI, and human-robot interaction.
Research Focus
Key Achievements
Top Papers
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