Papers
9
Total Citations
97
H-Index
5
About
Chunyong Feng is a robotics and intelligent systems researcher whose work sits at the intersection of autonomous navigation, fire safety, and smart building technologies. His most significant contributions center on firefighting and inspection robots capable of operating in hazardous, complex indoor environments. Feng's pioneering development of fire reconnaissance and firefighting robots — integrating SLAM (Simultaneous Localization and Mapping), thermal imaging, and flame recognition technologies — has garnered substantial attention, with his top papers accumulating 27 and 25 citations respectively. His 2022 proposal of the YOLOv4-F flame detection model demonstrated meaningful advances in real-time fire detection accuracy under challenging conditions, earning 22 citations. Beyond fire safety, Feng has extended his expertise to construction site inspection robots, evaluating LiDAR SLAM algorithms for large-scale public buildings and improving path planning through enhanced algorithms such as a modified A* and grey wolf optimization approach. His calibration work for MEMS-IMU systems further reflects a meticulous attention to the foundational precision underpinning autonomous robots. Across his body of work, Feng has established himself as a versatile researcher advancing practical robotic solutions that directly address real-world safety and infrastructure challenges.
Research Focus
Key Achievements
Top Papers
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- 4An Onsite Calibration Method for MEMS-IMU in Building Mapping Fields8 citations · 2019
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