Papers
3
Total Citations
18
H-Index
2
About
Yulin Li is a robotics researcher whose work focuses on enabling safe and efficient robot navigation in complex, cluttered, and unknown environments. Their key research areas include trajectory optimization, safety-critical control, and motion planning. Li’s major contributions center on developing mathematically rigorous frameworks that combine geometry-aware constraints with real-time perception. Their most cited work (2024, 9 citations) introduces a collision-free trajectory optimization method using sums-of-squares programming, which represents robot geometry as semialgebraic sets to handle general shapes in 3D environments. Another influential paper (2024, 7 citations) proposes a geometry-aware safety-critical reactive controller that formulates trajectory tracking as a constrained polynomial optimization problem, ensuring safe navigation without prior environmental knowledge. Their latest work, the FRTree Planner (2025, 2 citations), innovatively uses a tree of free regions to navigate narrow passages in unknown spaces by continuously integrating perceptive data. Li’s research stands out for its theoretical depth—leveraging polynomial optimization and formal safety guarantees—while addressing practical challenges in real-world robotics. Their growing citation record reflects the increasing relevance of their approaches to autonomous navigation in unstructured environments.
Research Focus
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Top Papers
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