Nonlinear model predictive control for sinusoidal gait tracking for an underwater snake robot

Abstract

Energy efficiency is crucial for the operational time and reach of autonomous underwater vehicles (AUVs). A new class of AUVs, underwater snake robots (USRs), has an articulated body that may be utilized to enhance propulsion efficiency and achieve energy autonomy. This paper applies nonlinear model predictive control (NMPC) to achieve sinusoidal gait tracking for underwater snake robots (USRs). We present a comprehensive simulation study that incorporates high-fidelity modeling of fluid-structure interaction, which validates the control design. Additionally, we showcase the potential for significant energy savings by fine-tuning the cost function, leading to reduced actuator power consumption.