Bogyeong Lee
Papers
1
Total Citations
2
H-Index
1
About
Bogyeong Lee is a researcher specializing in the intersection of robotics, artificial intelligence, and construction site safety. Her primary research areas include social navigation for robots in dynamic environments, reinforcement learning, and human-robot interaction within complex industrial settings. Lee’s most notable contribution is her work on developing context-appropriate navigation strategies for robots operating in construction environments, where varying human density and unpredictable layouts pose unique challenges. Her 2021 paper, “Context-appropriate Social Navigation in Various Density Construction Environment using Reinforcement Learning,” co-authored with Yeseul Kim, Robin Murphy, and Changbum Ahn, has garnered attention for its novel approach to enabling robots to adapt their movement patterns based on real-time social and spatial cues. This work is particularly impactful as it bridges the gap between theoretical reinforcement learning models and practical applications in hazardous, unstructured workspaces. Lee’s research holds significant promise for improving worker safety and operational efficiency on construction sites, with her findings contributing to the broader field of autonomous systems in challenging environments. Her achievements underscore a commitment to advancing robotic capabilities in real-world, high-stakes settings.
Research Focus
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Top Papers
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