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About

Yiwei Hao is a pioneering researcher in bio-inspired robotics, specializing in the design and control of robotic manta rays for agile underwater locomotion. Their major contributions center on developing biologically accurate propulsion systems that mimic the undulating pectoral fins of manta rays, enabling superior maneuverability and anti-interference performance in turbulent aquatic environments. Hao’s work on course control using amplitude and phase differences (32 citations) established a foundational framework for turning maneuvers, while their investigation of active–passive fin deformation (14 citations) revealed how flexible structures enhance thrust efficiency. By integrating closed-loop CPG-based control (12 citations) and optimizing CPG networks with particle swarm optimization (8 citations), Hao advanced autonomous swimming capabilities. Their application of T-S fuzzy neural networks (2 citations) further refined adaptive control in real-time conditions. With over 68 total citations across these key papers, Hao’s research directly addresses the challenge of external wave interference, offering practical solutions for underwater missions requiring stability and precision. Their bioinspired approach not only deepens understanding of manta ray locomotion but also provides a blueprint for next-generation autonomous underwater vehicles.