Efficient dense sonar surveys with an autonomous underwater vehicle

Abstract

An algorithm for the in situ adaptation of the survey route of an autonomous underwater vehicle (AUV) equipped with side-looking sonars was recently proposed. This algorithm immediately exploits the through-the-sensor data that is collected during a 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. In particular, the need to re-deploy the AUV (to fill gaps in the data coverage) is obviated. In turn, the time and costs of the data-collection mission are significantly reduced. In this work, we improve the aforementioned algorithm by introducing an additional constraint to the survey track-selection process. This modification significantly increases the efficiency of a survey by further reducing both transit time and the overall number of tracks executed. In particular, the revised algorithm more closely approximates the optimal survey route that would be executed if perfect knowledge of the future sonar performance during the mission were known a priori.