Papers
3
Total Citations
11
H-Index
2
About
Zonggang Li is a leading researcher in bio-inspired robotics, with a primary focus on the hydrodynamics and control of robotic fish. His work bridges the gap between biological locomotion and engineered systems, particularly in the challenging domain of BCF/MPF (Body and/or Caudal Fin – Median and/or Paired Fin) hybrid propulsion. Li’s major contributions include the development of data-driven dynamic models for precise trajectory tracking, where he innovatively integrates attention mechanisms and deep neural networks with nonlinear model predictive control. This approach, detailed in his most-cited 2025 paper (6 citations), enables unprecedented control of robotic fish by coupling CPG (Central Pattern Generator) networks with hydrodynamic identification. His numerical studies on pectoral fin and body motion gaits (4 citations) provide foundational insights into the synergistic control of fins and body, addressing the complex, multi-degree-of-freedom control problem that has long hindered the field. With a growing citation record, Li’s work is pivotal for advancing autonomous underwater vehicles, offering a blueprint for efficient, stable, and maneuverable robotic swimmers that can operate in real-world aquatic environments.
Research Focus
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Top Papers
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