Abstract
Hydrothermal vent areas are unique ecosystems with high productivity and high biodiversity that are subject to ongoing research. Hydrothermal vents form in areas with increased magmatic activity where superheated, mineral rich water leaks from the seafloor. Due to the rapid cooling of the water the metal sulfides precipitate and form a black or white plume that can be sensed several hundred meters away from the vent source. Finding and reliably following such plumes with autonomous underwater vehicles (AUVs) is a challenging task since the plume does not have a smooth concentration gradient but lots of local patches due to the turbulent particle flow. This paper presents an algorithm that combines biology inspired chemotaxis with Unscented Kalman filter (UKF) based extremum seeking control (ESC). The effectiveness is demonstrated by a simulation of a physics-based AUV model in a turbulent 3D Plume model.
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