Yanyan Cheng
Papers
2
Total Citations
33
H-Index
2
About
Yanyan Cheng is a leading researcher in heterogeneous collaborative robotics, specializing in energy-efficient perception and multi-modal map fusion for air-ground robotic systems. Her work addresses critical challenges in smart city applications, where unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) must collaborate seamlessly. Cheng’s most influential contribution is her pioneering framework for energy-efficient ground traversability mapping, which optimizes UGV path planning by integrating UAV aerial data to reduce energy consumption—a breakthrough cited 31 times. She further advanced the field with a multi-task Gaussian process classification approach for collaborative map fusion, enabling robust integration of heterogeneous sensor data from aerial and ground robots, despite its recent publication in 2020. This work overcomes the limitations of traditional isomorphic systems, allowing heterogeneous robotic teams to operate effectively in complex environments. Cheng’s research has direct implications for autonomous navigation, disaster response, and infrastructure inspection, where energy conservation and accurate environmental perception are paramount. Her innovative fusion of machine learning with robotic perception continues to shape the next generation of collaborative autonomous systems.
Research Focus
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Top Papers
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