Papers
29
Total Citations
555
H-Index
10
About
Tianjiang Hu is a robotics researcher whose work spans bioinspired underwater locomotion, multi-robot coordination, and autonomous navigation. He is perhaps best known for his pioneering investigations into undulating robotic fins modeled after *Gymnarchus niloticus*, a weakly electric fish whose ribbon-fin propulsion offers remarkable maneuverability. His 2008 study on the kinematics modeling and mechanism design of such fins has garnered 131 citations, establishing him as a leading voice in biomimetic underwater robotics. Complementing this, his computational hydrodynamics studies and learning control frameworks — which enable robotic fins to closely replicate live fish undulation patterns — further deepened understanding of biologically inspired propulsion systems. Beyond aquatic robotics, Hu has made significant contributions to multi-robot systems, developing exact and approximate algorithms for cooperative task allocation (62 citations) and pioneering reinforcement learning approaches for decentralized multi-robot pursuit, including attention-based methods that better capture inter-robot interactions. His work on visual odometry also reflects a broader interest in robot autonomy and perception. Collectively, Hu's research bridges biology, fluid dynamics, control theory, and artificial intelligence, making him a versatile and impactful contributor to modern robotics with over 450 cumulative citations across his most recognized works.
Research Focus
Key Achievements
Top Papers
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- 7Bionic asymmetry: from amiiform fish to undulating robotic fins18 citations · 2009
- 8Learning Control for Biomimetic Undulating Fins: An Experimental Study16 citations · 2010
- 9Visual odometry - A review of approaches15 citations · 2015
- 10DACOOP-A: Decentralized Adaptive Cooperative Pursuit via Attention10 citations · 2023