Papers

9

Total Citations

572

H-Index

7

About

Xi Fang is a robotics researcher whose work sits at the dynamic intersection of soft robotics, underwater autonomous systems, and computer vision. His research has made particularly significant contributions to the development of soft robotic manipulators designed for shallow-water aquaculture, addressing the urgent need to replace human divers in seafood harvesting operations at depths of approximately 30 meters. His 2020 paper on a soft manipulator for delicate underwater grasping has accumulated 224 citations, reflecting the field's enthusiasm for his integrated approach to modeling, control, and real-world validation. Fang has also advanced underwater robotic perception, notably through a GAN-based framework for real-time visual quality enhancement, which has garnered 141 citations and represents a practical breakthrough for vision-limited subsea environments. His broader portfolio spans bio-inspired soft robotic arm kinematics, variable stiffness grippers employing low-melting-point alloys, shape memory alloy continuum robots, and adaptive learning control strategies for grasping. With a cumulative citation count exceeding 570, Fang's work consistently bridges fundamental biomechanical modeling with deployable engineering solutions, making him an influential voice in next-generation soft robotics for challenging real-world applications.

Research Focus

Key Achievements

7
H-Index
9
Papers
572
Total Citations
64
Avg Citations/Paper
🏆 Most Cited Paper
A soft manipulator for efficient delicate grasping in shallow water: Modeling, control, and real-world experiments
224 citations · 2020
📈 Most Prolific Year: 2020 (2 Papers)
🤝 Key Collaborators: 31
🏛 Institutions: Beihang University, Beijing Institute of Technology

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago