AUV architecture

It is important for an AUV to be able to follow complex scenarios and to rapidly respond to emergency situations. The following architecture has been designed to reach these objectives.

In this section both sensor and deliberative layers are described. Literature on actuators and control systems for AUVs may be found in (Hamilton et al., 2007; Fossen, 2002). The trajectory generation is provided by the DFM algorithm. Sensor layer

The primary objective of the sensor layer is the generation of a local map. The output of this map provides an input for the deliberative layer that tries to match the arrangements of targets within the map against known scenarios. Our vehicle was equipped with inexpensive Tritech Sea King mechanically scanning forward looking sonar for obstacle detection. Navigation used an integrated GPS and Doppler Velocity Log solution mixing absolute and dead reckoning modes. Deliberative layer

To provide deliberation in the generation of a safe behavior, a subsumption (Brooks, 1986) deliberative architecture has been chosen. It includes a reactive layer above a scenario layer as depicted in figure 7.

The reactive layer is empowered to take over from the scenario layer in the event of emergency, thus safeguarding the vehicle. It is deigned as a fuzzy system and it is triggered by range to nearest object.

Fig. 7. Subsumption architecture implemented in the deliberative layer. A reactive layer is empowered to take over from the scenario layer in the event of emergency.

In the scenario layer, scripts called scenarios are employed. They are selected based on external and internal information along with mission requirements coming from the sensor layer. Ultimately, the deliberative layer sends the selected scenario and the selected target to the trajectory planning system, which generates the waypoints that are applied to the vehicle autopilot. Trajectory generation

The trajectory planning method used in this module is based on the DFM algorithm. Since the local map around the vehicle is regularly updated, the DFM algorithm fulfils its realtime trajectory replanning mission.

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