Motion Tomography Performed by Robotic Fish with Active Heading Control

Abstract

Water flow plays an important role in the operation of marine robotic vehicles (MRVs). In confined survey areas, accurate perception of the flow field can greatly assist MRVs in path planning and improve energy efficiency. Traditional flow observations rely on data from buoys and satellites, which is expensive and time-consuming. Therefore, predicting the flow field using the vehicle’s position and velocity information can significantly enhance work efficiency. Motion tomography (MT) is a time-efficient and convenient technique that estimates the flow field by separating the movement caused by the flow field from the trajectory of the MRV. Additionally, robotic fish are ideal for this flow field sensing task due to their maneuverability and versatility. Using robotic fish to sense the flow field can greatly benefit transportation and environment studies. However, MT ignores the rigid-body dynamics, which can significantly undermine the estimation accuracy. To address this challenge, we add an active heading control (AHC) to moderate the passive heading change caused by the flow field. With AHC’s help, the position and direction data collected from a robotic fish can provide a promising estimation of the flow field in both simulations and experiments.