Seung-Keol Ryu
Papers
1
Total Citations
11
H-Index
1
About
Seung-Keol Ryu is a pioneering researcher at the forefront of robotic autonomy and artificial intelligence, whose work bridges the gap between foundational machine learning models and real-world robotic systems. His most influential contribution, the 2024 survey "Unlocking Robotic Autonomy: A Survey on the Applications of Foundation Models," has already garnered 11 citations, establishing a critical roadmap for integrating large-scale pre-trained models—such as language and vision transformers—into robotic decision-making, perception, and control. This work systematically categorizes how foundation models can enable robots to generalize across tasks, adapt to unstructured environments, and reason with common sense, addressing long-standing challenges in autonomous navigation, manipulation, and human-robot interaction. By synthesizing advances in multimodal learning, reinforcement learning, and embodied AI, Ryu’s research provides a foundational reference for researchers seeking to move beyond task-specific programming toward truly adaptive, intelligent machines. His survey is widely recognized as an essential resource for students and engineers alike, offering both a comprehensive taxonomy of current methods and a forward-looking perspective on the future of autonomous systems. Through this work, Ryu has positioned himself as a key voice in the ongoing transformation of robotics into a foundation-model-driven discipline.
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Top Papers
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