Matching the swimming efficiency and agility of fish has remained an elusive goal in underwater robotics. Such locomotion capabilities require complex vortex interactions between the robot's body and the surrounding fluid. Despite significant advances in biomimetic hardware, realizing successful robot policies faces several additional challenges, which include: the need for accurate and efficient simulation of fluid-robot multiphysics; utilizing the simulators effectively for downstream policy design; and successfully transferring policies from simulation to real hardware.

This thesis addresses these challenges by developing a differentiable fluid–robot interaction simulator and applying it to achieve bioinspired aquatic locomotion. We first present a novel multiphysics framework that solves the strongly coupled fluid–robot dynamics as a single, differentiable optimization problem. We then exploit the simulator's differentiability to optimize control trajectories for a robotic eel, achieving various swimming behaviors, including steady undulatory locomotion and a highly dynamic C-start escape maneuver. To validate the simulation results, we design and fabricate an accessible, from-scratch hardware platform. This culminates in successful bioinspired robotic swimming in the real world.

Together, these contributions advance the state of the art in simulation of underwater robots while providing a new sim-to-real platform for future research in bioinspired aquatic locomotion.