Numerical Study of Yaw Control in Rajiform Swimmers for Batoid-Inspired AUV Guidance

Unmanned Underwater Vehicles (UUVs) are essential tools for seabed exploration, naval operations, and environmental monitoring, offering lower operational costs and reduced human risk. These vehicles are typically categorized as Remotely Operated Vehicles (ROVs) or Autonomous Underwater Vehicles (AUVs). This study focuses on AUVs, which operate based on a pre-programmed decision-making algorithm. Traditional AUVs are modeled after existing torpedo designs, utilizing a rigid hull and propeller-based thrust system. In contrast, aquatic animals with flexible body morphologies were observed to outperform traditional AUVs. Our study focuses on undulatory batoids (Rajiform) as inspiration for AUVs, considering that they are well-adapted to operate in benthic regions, offering high stability and minimal acoustic signature. Conventional AUVs use line-of-sight (LOS) guidance to determine heading and apply the necessary corrective torque, typically by adjusting the propeller speed. In contrast, control for batoid-inspired AUVs is much more complex, as corrective torques must be generated by modulating wave parameters across the pectoral fins, resulting in yaw rate and torque with inherent periodicity. In this study, we conduct high-fidelity fluid-structure interaction simulations of a self-propelled stingray using our in-house Immersed Boundary (IB) code. Studying a rajiform swimmer executing asymmetric gaits across its pectoral fins, we intend to obtain an understanding of how thrust generation varies as the swimmer performs a yawing maneuver. By investigating the coherent structures in the swimmer’s wake, we aim to inform the design of control algorithms for batoid-inspired AUVs.