Qinbing Fu
Papers
30
Total Citations
579
H-Index
14
About
Qinbing Fu is a computational neuroscientist and robotics researcher whose work sits at the intersection of biological vision, neural modeling, and autonomous systems. His research focuses primarily on bio-inspired visual neural networks, collision perception, and motion detection, drawing inspiration from insect visual systems — particularly the locust's lobula giant movement detector (LGMD) neurons. Fu has made substantial contributions to modeling how insects detect looming threats and directional motion, translating these biological mechanisms into robust algorithms for robotics and autonomous vehicles. His highly cited 2019 review on insect visual systems for motion perception (69 citations) established him as a key synthesizer in the field, while his work on LGMD1 and LGMD2 neuron models has advanced collision-selective visual systems with real-world applicability. Notably, his research on darker-object selectivity (63 citations) and parallel ON/OFF pathway architectures (67 citations) has refined the specificity and reliability of artificial collision detectors. Fu has also demonstrated a strong translational vision through platforms like the Colias IV micro robot, bridging computational modeling with physical autonomous systems. Collectively, his publications have accumulated nearly 400 citations, reflecting meaningful and growing influence across neurorobotics and computer vision communities.
Research Focus
Key Achievements
Top Papers
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- 6Colias IV: The Affordable Micro Robot Platform with Bio-inspired Vision30 citations · 2018
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- 9Modelling LGMD2 visual neuron system25 citations · 2015
- 10Energy-Efficient Design and Control of a Vibro-Driven Robot21 citations · 2018