Targeted sampling by autonomous underwater vehicles

Abstract

In the vast ocean, many ecologically important phenomena are temporally episodic, localized in space, and move according to local currents. To effectively study these complex and evolving phenomena, methods that enable autonomous platforms to detect and respond to targeted phenomena are required. Such capabilities allow for directed sensing and water sample acquisition in the most relevant and informative locations, as compared against static grid surveys. To meet this need, we have designed algorithms for autonomous underwater vehicles that detect oceanic features in real time and direct vehicle and sampling behaviors as dictated by research objectives. These methods have successfully been applied in a series of field programs to study a range of phenomena such as harmful algal blooms, coastal upwelling fronts, and microbial processes in open-ocean eddies. In this review we highlight these applications and discuss future directions.