Cuiyun Fang

University of Science and Technology of China

Papers

Total Citations

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About

Dr. Cuiyun Fang is a leading researcher in autonomous robotics, specializing in visual navigation and perception-aware systems for mobile robots. Her work addresses a critical challenge: enabling reliable, real-time navigation without reliance on pre-built metric maps or extensive training datasets. In her highly cited 2022 paper, “Object-Based Reliable Visual Navigation for Mobile Robot,” Dr. Fang introduces a novel framework that leverages object-level semantic cues to enhance navigation robustness in dynamic, unstructured environments. This approach significantly reduces computational overhead while improving adaptability, marking a departure from traditional metric-map-dependent methods. With 24 citations in just two years, her research is gaining rapid traction among robotics engineers and AI researchers. Dr. Fang’s contributions are particularly impactful for applications in search-and-rescue, industrial automation, and autonomous exploration, where reliability under uncertainty is paramount. Her work exemplifies a shift toward more efficient, generalizable visual navigation, positioning her as a rising authority in the field.