Ki Myung Brian Lee
Papers
5
Total Citations
65
H-Index
4
About
Ki Myung Brian Lee is a robotics researcher whose work centers on advancing multi-robot coordination, autonomous navigation, and unified scene representation. His most impactful contribution is the "Broadcast Your Weaknesses" framework for cooperative active pose-graph SLAM, which enables multiple robots to efficiently explore 3D environments by focusing on weak topological connections—a method that has garnered 30 citations for its low-cost, high-efficiency approach. Lee further innovated with Log-GPIS-MOP, a unified representation that simultaneously handles mapping, odometry, and planning, earning 19 citations and challenging the need for task-specific models. His research also tackles trajectory prediction in cluttered spaces by leveraging homotopy classes to simplify infinite trajectory possibilities, and he has developed an upper confidence bound algorithm for heterogeneous multi-robot systems that balances exploration and exploitation. Additionally, Lee addresses the robot task sequencing problem for manipulators using Gromov-Hausdorff approximations. His work, published in top venues like *IEEE Robotics and Automation Letters*, demonstrates a consistent drive to create scalable, theoretically grounded solutions for complex robotic challenges, making him a rising figure in autonomous systems research.
Research Focus
Key Achievements
Top Papers
- 1
- 2Log-GPIS-MOP: A Unified Representation for Mapping, Odometry, and Planning19 citations · 2023
- 3Topological Trajectory Prediction with Homotopy Classes6 citations · 2023
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