  Expansion of today's underwater scenarios and missions necessitates the
requestion for robust decision making of the Autonomous Underwater Vehicle
(AUV); hence, design an efficient decision making framework is essential for
maximizing the mission productivity in a restricted time. This paper focuses on
developing a deliberative conflict-free-task assignment architecture
encompassing a Global Route Planner (GRP) and a Local Path Planner (LPP) to
provide consistent motion planning encountering both environmental dynamic
changes and a priori knowledge of the terrain, so that the AUV is reactively
guided to the target of interest in the context of an unknown underwater
environment. The architecture involves three main modules: The GRP module at
the top level deals with the task priority assignment, mission time management,
and determination of a feasible route between start and destination point in a
large scale environment. The LPP module at the lower level deals with safety
considerations and generates collision-free optimal trajectory between each
specific pair of waypoints listed in obtained global route. Re-planning module
tends to promote robustness and reactive ability of the AUV with respect to the
environmental changes. The experimental results for different simulated
missions, demonstrate the inherent robustness and drastic efficiency of the
proposed scheme in enhancement of the vehicles autonomy in terms of mission
productivity, mission time management, and vehicle safety.
