Magnetic, modular, undulatory robots as robophysical models for exploration of fish-inspired swimming.

Evolution has successfully explored various forms of fluid-structure interaction (FSI) for underwater locomotion, from which a great diversity of fish swimming has emerged. However, it remains unclear how fish or fish-inspired swimming emerges from the complex physics of FSI which includes interactions among active structures (e.g., fins and elongated bodies), neuromuscular and motor control, and the physics of fluids. We address this problem using robophysical models of undulatory swimming (magnetic, modular, undulatory robots). Via experimental motor learning, we systematically explored the relationship among the body morphology, motor control, swimming gaits and performance. First, we studied the effects of the robot design (e.g., body length, caudal fin stiffness) on the emergence of swimming gaits and performance (e.g., forward/backward swimming, turning maneuver). Second, we identified the embodied properties in the FSI of the emergent gaits using motor learning, frequency response and motor control perturbation. Third, we employed time-resolved Particle Image Velocimetry (PIV) to quantitatively study the hydrodynamic properties for a diversity of emergent swimming gaits. These results provide novel insights and guiding principles for fish and fish-inspired robot swimming.