Papers
2
Total Citations
10
H-Index
2
About
Pengfan Wu is a rising innovator at the intersection of bio-inspired engineering and self-powered sensing, whose work is shaping the future of intelligent robotics. His primary research focuses on triboelectric nanogenerators (TENGs) and biomimetic surface engineering, with a particular emphasis on developing self-powered sensors for motion and gait recognition in legged and field robots. Wu’s major contributions include the design of a bio-inspired triboelectric sensor that functions as a self-powered gait recognition system, enabling robots to autonomously detect and adapt to terrain without external power sources. He further advanced the field by enhancing sensor hydrophobicity through biomimetic structures, improving durability and sensitivity for real-world field applications. Though early in his career, his work has already garnered attention, with his most cited paper accumulating 7 citations shortly after publication in 2025. This recognition underscores the novelty and potential impact of his approach. Wu’s notable achievement lies in seamlessly merging principles from nature with triboelectric technology, paving the way for more autonomous, energy-efficient, and resilient robotic systems. His research promises to revolutionize how robots interact with complex environments, making him a researcher to watch in the rapidly evolving field of self-powered robotics.
Research Focus
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Top Papers
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