  Ocean ecosystems have spatiotemporal variability and dynamic complexity that
require a long-term deployment of an autonomous underwater vehicle for data
collection. A new long-range autonomous underwater vehicle called Tethys is
adapted to study different oceanic phenomena. Additionally, an ocean
environment has external forces and moments along with changing water currents
which are generally not considered in a vehicle kinematic model. In this
scenario, it is not enough to generate a simple trajectory from an initial
location to a goal location in an uncertain ocean as the vehicle can deviate
from its intended trajectory. As such, we propose to compute a feedback plan
that adapts the vehicle trajectory in the presence of any modeled or unmodeled
uncertainties. In this work, we present a feedback motion planning method for
the Tethys vehicle by combining a predictive ocean model and its kinematic
modeling. Given a goal location, the Tethys kinematic model, and the water flow
pattern, our method computes a feedback plan for the vehicle in a dynamic ocean
environment that reduces its energy consumption. The computed feedback plan
provides the optimal action for the Tethys vehicle to take from any location of
the environment to reach the goal location considering its orientation. Our
results based on actual ocean model prediction data demonstrate the
applicability of our method.
