Papers
8
Total Citations
43
H-Index
4
About
Jianjun Fang is a robotics researcher whose work sits at the intersection of computer vision, control systems, and autonomous navigation. His primary contributions focus on enabling robots to perceive and interact with their environments more intelligently. Fang is best known for developing a Speeded Up SURF (SSURF) algorithm for robust object recognition under challenging conditions like scale changes and poor illumination, a foundational contribution that has garnered 13 citations. He has also pioneered the application of Extreme Learning Machines (ELM) for real-time field terrain recognition, a critical capability for legged and off-road robots operating in unstructured environments. Beyond perception, Fang has designed intelligent control systems, including a parameter self-tuning fuzzy-PID controller for a library robot’s pneumatic manipulator, and has explored machine vision for specialized applications like Chinese chess-playing robots. His work on terrain classification using wavelet and texture features, alongside contributions to wireless sensor network security, demonstrates a broad engineering focus. With a career spanning from 2009 to 2018, Fang’s research has directly advanced the practical deployment of robots in complex, real-world settings, making his work essential reading for students interested in vision-based robotics and autonomous mobility.
Research Focus
Key Achievements
Top Papers
- 1Robot robust object recognition based on fast SURF feature matching13 citations · 2013
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- 6A Machine Vision System for Chinese Chess-Playing Robot4 citations · 2012
- 7A Security Mechanism Based on Authenticated Diffie-Hellman for WSN3 citations · 2013
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