Papers
12
Total Citations
295
H-Index
8
About
Yanyu Su’s research lies at the intersection of robotics, machine learning, and human-robot interaction, with a core focus on developing intelligent robotic systems for safety-critical and assistive applications. He is best known for his pioneering work on search-and-rescue robots for underground coal mines, where he designed two generations of tracked mobile robots to replace human rescuers in high-risk environments—a contribution that has garnered 87 citations and demonstrated significant real-world impact. Su has also made substantial advances in robot imitation learning, introducing a syntactic approach using probabilistic activity grammars (63 citations), and in online learning for tactile classification through spatio-temporal Gaussian process experts (55 citations). His work on robust grasping with under-actuated anthropomorphic hands (23 citations) and dexterous manipulation under object position uncertainty addresses fundamental challenges in robotic manipulation. Additionally, Su contributed to open-architecture robotic systems, developing universal kinematic controllers and teach pendants that enhance robot interoperability. With over 280 total citations across his most-cited works, Yanyu Su’s research continues to influence both field robotics and the broader robotics community.
Research Focus
Key Achievements
Top Papers
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- 9U-Pendant: A universal teach pendant for serial robots based on ROS6 citations · 2014
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