  Today AUVs operation still remains restricted to very particular tasks with
low real autonomy due to battery restrictions. Efficient motion planning and
mission scheduling are principle requirement toward advance autonomy and
facilitate the vehicle to handle long-range operations. A single vehicle cannot
carry out all tasks in a large scale terrain; hence, it needs a certain degree
of autonomy in performing robust decision making and awareness of the
mission/environment to trade-off between tasks to be completed, managing the
available time, and ensuring safe deployment at all stages of the mission. In
this respect, this research introduces a modular control architecture including
higher/lower level planners, in which the higher level module is responsible
for increasing mission productivity by assigning prioritized tasks while
guiding the vehicle toward its final destination in a terrain covered by
several waypoints; and the lower level is responsible for vehicle's safe
deployment in a smaller scale encountering time-varying ocean current and
different uncertain static/moving obstacles similar to actual ocean
environment. Synchronization between higher and lower level modules is
efficiently configured to manage the mission time and to guarantee on-time
termination of the mission. The performance and accuracy of two higher and
lower level modules are tested and validated using ant colony and firefly
optimization algorithm, respectively. After all, the overall performance of the
architecture is investigated in 10 different mission scenarios. The analyze of
the captured results from different simulated missions confirm the efficiency
and inherent robustness of the introduced architecture in efficient time
management, safe deployment, and providing beneficial operation by proper
prioritizing the tasks in accordance with mission time.
