Experimental Pitch and Heading Control of Subcarangiform Robotic Fish for Underwater Perception Arrays

When using underwater perception to detect and classify submerged unidentified objects, arranging a sensor with respect to a global reference frame is crucial for obtaining accurate target information. When employing Uncrewed Underwater Vehicles (UUVs) to create a sensor array, knowing and controlling the platform's Angle of Attack (AoA) during data collection is essential. This study examines the use of the University of New Hampshire's biomimetic robotic fish, the Ghost Uncrewed Performance Platform Submersible (GUPPS), to unobtrusively gather underwater perception data. Building on a 5-DOF simulation model of GUPPS, the mapping between motor input and resulting angular output in pitch and heading is characterized experimentally. The relationship between the fin input and GUPPS’ corresponding output agree between experimental trials and simulation results. This relationship is utilized to develop a controller that manages GUPPS’ AoA in relation to a global reference frame.