Hang Li
Papers
13
Total Citations
292
H-Index
6
About
Hang Li is a versatile robotics and artificial intelligence researcher whose work spans autonomous navigation, wireless sensor networks, and generative AI for robot manipulation. His most significant contributions lie in developing safe navigation algorithms for mobile and aerial robots operating in complex, dynamic environments — work that has earned substantial recognition within the field. His 2018 paper on wireless sensor network-based navigation of micro flying robots in the Industrial Internet of Things stands as his most impactful contribution, accumulating 110 citations, while his complementary work on sensor network-guided navigation in cluttered industrial environments has garnered an additional 60 citations. Li has also made notable advances in underground mine exploration, proposing methods for autonomous UAVs to map hazardous tunnel environments — critical work for industrial safety applications. More recently, his research trajectory has expanded dramatically into large-scale generative AI, with his GR-2 model leveraging 38 million video clips and 50 billion tokens to train generalizable robot manipulation agents. This evolution from classical navigation algorithms to cutting-edge video-language-action models demonstrates Li's remarkable breadth, positioning him as a researcher bridging traditional robotics with the emerging frontier of foundation models for embodied intelligence.
Research Focus
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Top Papers
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- 10An Optical Flow based Tunnel Navigation Algorithm for a Flying Robot3 citations · 2018