Framework for multi-vehicle adaptive sampling of jets and plumes in coastal zones

Abstract

This thesis presents a framework for the sampling of thermal and effluent jets and plumes using multiple autonomous surface vehicles. The framework was developed with the goal of achieving rapid and accurate in-situ measurement and characterization of these features. The framework is presented as a collection of simulation, estimation and field tools for use within the Mission Oriented Operations Suite (MOOS) and a novel Acoustic Doppler Current Profiling system that is capable of reorientation and real-time feedback. Key features developed within MOOS include a multi-parameter model of thermal and effluent jet and plume fields, online parameter estimation and sensor fusion. Using these tools, a collaborative adaptive sampling strategy is implemented to efficiently sample an industrial jet and plume. The capabilities of this strategy are demonstrated in realistic mission simulations and in field trials using a fleet of autonomous kayaks equipped with environmental sensors.