Real-time center of buoyancy identification for optimal hovering in autonomous underwater intervention

Abstract

This work addresses the problem of optimal positioning for an intervention AUV, minimizing the energy consumption and improving the stability in orientation. During a generic intervention task, the vehicle is generally maintained in a hovering configuration, thus requiring a 6 DOF control of the vehicle positioning. The choice of roll and pitch, if done arbitrarily, can severely impact the power efficiency of the vehicle, especially in heavy systems, since the center of buoyancy (COB) may not be necessarily aligned over the center of mass (COM). This approach uses an Extended Kalman Filter (EKF) to identify the location of the center of buoyancy relative to the center of mass, thus allowing to compute the working orientation that maintains the COB vertically aligned above the COM. The EKF is implemented online and hence is able to detect movements of the COB due for example to ballast operations. This algorithm has been firstly implemented in simulation and then successfully validated with the SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions) autonomous underwater vehicle. With its weight of about 4 tons, this testbed is an optimal platform for validating the precision of the filter, since a very small variation of the target pitch and roll results in a large restoring torque.