Papers
13
Total Citations
265
H-Index
9
About
Haibin Xie is a pioneering researcher in the field of bionic underwater robotics, with a distinguished focus on biomimetic propulsion systems, neural control architectures, and computational hydrodynamics. His work centers on translating the extraordinary locomotion capabilities of aquatic animals — particularly undulating fin mechanics — into functional robotic systems, bridging the gap between biological inspiration and engineering application. Xie's most influential contributions include the design of artificial bionic neural networks for controlling fish-robot locomotion and the development of supervised neural Q-learning frameworks for motion control in underwater robots, each garnering over 40 citations. His rigorous computational and experimental investigations into undulating fin dynamics have established foundational insights into median and paired fin (MPF) propulsion, demonstrating its remarkable advantages in vector thrust generation and minimal flow disturbance. Notably, his 2010 two-dimensional computational hydrodynamics study further solidified theoretical understanding of these systems. With work spanning swim bladder dynamics modeling, central pattern generator (CPG) control methods, and experimental learning control, Xie has assembled a coherent and impactful body of research. Accumulating over 240 citations across a decade of publications, his contributions remain essential reading for researchers advancing the frontier of biomimetic underwater vehicle design.
Research Focus
Key Achievements
Top Papers
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- 6Learning Control for Biomimetic Undulating Fins: An Experimental Study16 citations · 2010
- 7A bionic neural network for fish-robot locomotion16 citations · 2006
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- 9Dynamics and initial experiments of bionic undulating fish fin10 citations · 2013
- 10CPGs control method using a new oscillator in robotic fish9 citations · 2010