Plume source localization for AUV based autonomous hydrothermal vent discovery

Hydrothermal vent systems are the plumbing systems of the deep ocean, spewing heat and minerals from Earth´s interior while supporting unique ecosystems and offering clues about the geological processes that regulate the formation of oceanic crust. Locating and mapping the distribution of hydrothermal plumes near the venting sources assists the geochemists optimize their efforts to study the evolution of dissolved and particulate components of vent emissions by helping them determine the best locations and depths to take water samples. This paper presents an effective hydrothermal plume mapping and search algorithms for using on AUVs to locate the hydrothermal venting source location. AUVs use hydrothermal chemical signature as a guide to navigate and track in the unknown environments. The mapping algorithms are based on Bayesian inference theory. The planning algorithms are based on artificial potential field methods. This methodology results in algorithms for predicting likelihood of vent location versus position. The AUV would then optimize a desired trajectory to navigate in the hydrothermal plume and locate the hydrothermal vent.