Yeseul Kim
Papers
2
Total Citations
5
H-Index
2
About
Yeseul Kim is a researcher advancing human-robot interaction (HRI) within complex, unstructured construction environments. Her work focuses on two critical challenges: enabling intuitive communication between workers and robots, and ensuring robots can navigate safely and socially alongside humans on dynamic job sites. In her highly cited 2021 paper, "Challenges in Deictic Gesture-Based Spatial Referencing for HRI in Construction," Kim identifies key barriers to using natural pointing gestures for spatial communication—a foundational step toward more seamless collaboration. Her second major contribution, "Context-appropriate Social Navigation in Various Density Construction Environment using Reinforcement Learning," pioneers the use of reinforcement learning to train robots to adapt their movement patterns based on real-time human density and activity, moving beyond static navigation rules. With a combined early citation impact of 5 citations, Kim’s work is already shaping the next generation of construction robotics. By tackling both communication and navigation, she is helping to build the foundational frameworks for robots that can truly work alongside people in the messy, unpredictable reality of construction sites.
Research Focus
Key Achievements
Top Papers
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