We consider the task of conducting underwater surveys with a sonar-equipped autonomous underwater vehicle (AUV) in environments with strong currents. More specifically, this topic is addressed in the context of mine countermeasure operations employing synthetic aperture sonar (SAS) sensors. Two complementary algorithms that allow the AUV to autonomously adapt its survey route based on sophisticated sensor data it collects in situ, while respecting the unique constraints imposed by the problem, are proposed. The algorithms allow the AUV to (i) adapt its survey heading based on the presence of currents to ensure quality data is collected, and (ii) adapt its survey route to reinspect the most suspicious objects at additional aspects. The flexibility to immediately react in situ to the environmental and tactical conditions sensed during the mission allow the most useful data for object recognition purposes to be collected efficiently. By obviating the recovery and redeployment of the AUV, as well as laboratory-based data-processing during the interregnum, the overall mission timeline can be greatly compressed and operational costs can be reduced. Experimental results illustrating the real-time execution of the proposed algorithms on an AUV are shown for a completely autonomous mission conducted in the North Sea.

An algorithm for the in situ adaptation of the survey route of an autonomous underwater vehicle (AUV) equipped with side-looking sonars is proposed. The algorithm immediately exploits the through-the-sensor data that is collected during the mission in order to ensure that quality data is collected everywhere in the area of interest. By introducing flexibility into the survey of the AUV, various limitations of pre-planned surveys are overcome. Experimental results demonstrate the benefit of the proposed approach in terms of higher area coverage in shorter mission times. The signal processing required by the algorithm is fast and computationally efficient such that real-time implementation is feasible. As proof, the proposed adaptive survey approach was implemented on an AUV and executed during a recent live scientific experiment at sea using real, in situ measured data. Results from this experiment are also shown.