Sangbeom Park
Papers
4
Total Citations
32
H-Index
4
About
Sangbeom Park is a leading researcher at the intersection of robotics, human-robot interaction, and large language models (LLMs). His work focuses on making interactive robotic agents more reliable and intuitive by addressing fundamental challenges in user command understanding and autonomous task execution. Park’s major contributions include the development of CLARA, a novel framework that uses uncertainty estimation in LLMs to classify whether user commands are clear, ambiguous, or infeasible—a critical step toward trustworthy, real-time human-robot collaboration. He also introduced SPOTS, which tackles the underexplored problem of stable object placement in semi-autonomous teleoperation systems, and pioneered a quality-diversity approach to teleoperation using reinforcement learning, enabling robots to generate diverse, user-controllable behaviors rather than repetitive solutions. With over 30 citations across his most-cited works, Park’s research has been recognized for its practical impact on assistive robotics and autonomous systems. His work is particularly notable for bridging the gap between high-level language understanding and low-level robotic control, paving the way for more adaptable and user-friendly robotic assistants in real-world environments.
Research Focus
Key Achievements
Top Papers
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