Papers
79
Total Citations
4,107
H-Index
37
About
Hang Su is a prominent robotics researcher whose work spans surgical robotics, human-robot interaction, autonomous control systems, and agricultural automation. His research has made transformative contributions to teleoperated minimally invasive surgery, where he has pioneered human-robot collaborative control frameworks leveraging redundant manipulators and remote center of motion constraints — work that has collectively garnered hundreds of citations and directly advances safer, more intelligent surgical systems. His highly cited 2019 paper on hierarchical operational space control (229 citations) and subsequent neural network-based approaches (205 citations) demonstrate a consistent drive to make surgical robots both smarter and more clinically reliable. Su has also championed learning-from-demonstration methodologies, enabling robots to acquire surgical manipulation skills intuitively from human experts. Beyond the operating room, his influential contributions extend to multilegged robot dynamics, mobile robot stability control, and wheel-legged autonomous systems, reflecting exceptional breadth across robotic platforms. His 2023 survey on agricultural robots (198 citations) highlights his engagement with real-world societal challenges in precision farming. With research touching machine learning, fuzzy logic, and multimodal human-robot interaction, Su represents a uniquely versatile voice shaping the next generation of intelligent, collaborative robotic systems across healthcare, industry, and beyond.
Research Focus
Key Achievements
Top Papers
- 1
- 2Toward Teaching by Demonstration for Robot-Assisted Minimally Invasive Surgery217 citations · 2021
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- 5Recent Advancements in Agriculture Robots: Benefits and Challenges198 citations · 2023
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- 8Recent advancements in multimodal human–robot interaction155 citations · 2023
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