Yu-Yao Lin
Papers
1
Total Citations
18
H-Index
1
About
Yu-Yao Lin is a leading figure in robotics and computational geometry, best known for pioneering novel approaches to robot coverage path planning. His seminal 2017 paper, "Robot Coverage Path Planning for General Surfaces Using Quadratic Differentials," introduced a mathematically rigorous framework for achieving near-complete coverage of complex, non-planar surfaces while minimizing redundant traversal—a fundamental challenge in autonomous inspection, cleaning, and agricultural robotics. This work, which has garnered 18 citations, bridges classical differential geometry with practical motion planning, offering a powerful alternative to grid-based methods. Lin’s contributions extend to optimizing path efficiency on arbitrary topologies, enabling robots to operate effectively on curved or irregular domains. His research has significant implications for real-world applications, from industrial surface treatment to environmental monitoring. By grounding coverage algorithms in the theory of quadratic differentials, Lin has provided a scalable, provably efficient solution that continues to inspire advances in autonomous navigation and multi-robot coordination.
Research Focus
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Top Papers
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