Papers
5
Total Citations
292
H-Index
4
About
Humphrey Hu is a robotics researcher whose work spans surgical robotics, multi-robot systems, and perception. His most impactful contribution is the seminal 2010 paper on "Superhuman performance of surgical tasks by robots using iterative learning from human-guided demonstrations," which has accumulated 243 citations. This work pioneered an apprenticeship learning approach enabling robotic surgical assistants to perform specific subtasks—such as retraction and suturing—with superhuman precision, promising to reduce surgeon tedium and shorten operation durations. Hu has also made notable contributions to cooperative control, as seen in his work on ornithopter MAVs and lightweight ground stations for narrow passage traversal, and to mobile manufacturing, where he proposed replacing large, costly fixtures with numerous small mobile robots for assembling large structures. More recently, Hu has focused on perception system robustness, developing introspective evaluation methods for parameter tuning without ground truth and exploring how context affects perception performance. His research demonstrates a consistent thread of enabling robots to operate more autonomously and effectively in complex, real-world environments, from the operating room to the factory floor.
Research Focus
Key Achievements
Top Papers
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- 3Mobile manufacturing of large structures14 citations · 2015
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