Tianming Feng
Papers
4
Total Citations
25
H-Index
2
About
Tianming Feng is a leading researcher in robotics and power infrastructure inspection, specializing in the development of flying–walking hybrid robots for overhead power transmission line maintenance. His key research areas include multiobjective energy optimization, 3D reconstruction, autonomous navigation, and path-following control for inspection robots. Feng’s major contributions center on improving the efficiency and reliability of hybrid robots that combine the flight capabilities of UAVs with the climbing abilities of multi-arm robots. His most-cited work (14 citations) proposes an improved NSGA-II algorithm to optimize energy consumption during flight missions, significantly enhancing operational endurance. He also pioneered a Neural Radiance Fields-based method for 3D reconstruction of power lines from sequential images, addressing challenges in unbounded scenes and thin-structure feature matching (7 citations). Additionally, Feng developed an improved line-of-sight path-following controller and a novel autonomous landing method using prior structural data, both critical for stable operation in complex transmission line environments. His research has accumulated over 25 citations and represents a significant advance in autonomous power grid inspection, offering practical solutions for reducing human risk and improving maintenance efficiency in challenging outdoor settings.
Research Focus
Key Achievements
Top Papers
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