Papers
80
Total Citations
2,109
H-Index
27
About
Shigang Yue is a distinguished researcher whose work spans bio-inspired visual computing, swarm robotics, and assistive robotics. He is perhaps best known for his pioneering contributions to computational modeling of the locust's lobula giant movement detector (LGMD) neuron, a biological visual system that responds powerfully to approaching objects. His early work adapting this model for collision detection in complex dynamic environments — including automotive applications — has garnered over 150 citations and laid the groundwork for a generation of bio-inspired machine vision systems. Yue has consistently advanced these models, refining their selectivity, robustness, and applicability to autonomous vehicles and micro-robots, with multiple papers in this area each attracting 60–80 citations. His 2019 review of insect visual motion perception systems has further cemented his role as a leading synthesizer in the field. Beyond biological vision, Yue has made significant contributions to swarm robotics, developing the low-cost Colias micro-robot platform and novel aggregation algorithms. His involvement in the ENRICHME assistive robotics project, with over 120 citations, demonstrates a compelling breadth — applying intelligent robotics to enhance the lives of elderly individuals. Together, his body of work represents a rich intersection of neuroscience, engineering, and humanitarian application.
Research Focus
Key Achievements
Top Papers
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- 3Colias: An Autonomous Micro Robot for Swarm Robotic Applications88 citations · 2014
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- 5Cue-based aggregation with a mobile robot swarm: a novel fuzzy-based method75 citations · 2014
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