Fish Locomotion

Fish locomotion research aims to understand the diverse mechanisms enabling aquatic animals to move efficiently and maneuver effectively in water, informing the design of bio-inspired robots and advancing our understanding of biological systems. Current research focuses on optimizing robotic designs through biomimetic approaches, employing various control strategies including reinforcement learning and differentiable physics simulations to improve swimming performance and efficiency across different Reynolds numbers and locomotion styles (e.g., undulatory, drag-based). These studies leverage advanced modeling techniques, such as fluid-structure interaction simulations and neural networks, to analyze and optimize swimming gaits, contributing to both fundamental biological knowledge and the development of versatile underwater robots for diverse applications.