Autonomous Marine Sampling Enhanced by Strategically Deployed Drifters in Marine Flow Fields
This work addresses ocean sampling for marine research, presenting an incremental improvement in autonomous sensing systems.
The paper tackles the problem of ocean observation by using an autonomous surface vehicle to strategically deploy passive drifters for enhanced spatial coverage, achieving increased information gain in simulated flow field experiments.
We present a transportable system for ocean observations in which a small autonomous surface vehicle (ASV) adaptively collects spatially diverse samples with aid from a team of inexpensive, passive floating sensors known as drifters. Drifters can provide an increase in spatial coverage at little cost as they are propelled about the survey area by the ambient flow field instead of with actuators. Our iterative planning approach demonstrates how we can use the ASV to strategically deploy drifters into points of the flow field for high expected information gain, while also adaptively sampling the space. In this paper, we examine the performance of this heterogeneous sensing system in simulated flow field experiments.