Hannah Lee
Papers
1
Total Citations
54
H-Index
1
About
Hannah Lee is a leading researcher in multi-robot systems, with a focus on integrated task and motion planning. Her most-cited work, "Multi-Robot Task and Motion Planning With Subtask Dependencies" (2020, 54 citations), introduces TMP-CBS, a novel framework that extends Conflict Based Search to handle sequential subtask dependencies within decomposable tasks. This contribution bridges a critical gap between high-level task allocation and low-level motion coordination, enabling robots to efficiently collaborate on complex, interdependent operations. Lee’s approach has significant implications for warehouse automation, disaster response, and manufacturing, where multiple robots must dynamically adapt to shared goals. Her work is recognized for its clarity and practical impact, earning her a reputation for advancing scalable multi-robot coordination. With 54 citations and growing influence, Lee continues to shape the future of autonomous robotic teamwork, inspiring students and researchers to explore the intersection of task decomposition and motion feasibility.
Research Focus
Key Achievements
Top Papers
- 1Multi-Robot Task and Motion Planning With Subtask Dependencies54 citations · 2020