Multi-vehicle autonomous sampling of a coastal thermal and effluent jet and plume

Conference paper (2012)

Authors

Matthew Gildner Massachusetts Institute of Technology
Gabriel D. Weymouth MIT Alliance for Research and Technology (SMART)
N. Patrikalakis Massachusetts Institute of Technology
Affiliation
External organisation
More Info
expand_more

Published Date

2012

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Affiliation

External organisation

Abstract

Adaptive sampling algorithms and behavior-based approaches can aid in the rapid and accurate in-situ measurement and characterization of coastal environmental features such as industrial thermal effluent jets and plumes. To enable the development of these techniques we present a collection of simulation, estimation, and field tools for use within the Mission Oriented Operations Suite (MOOS). Key features include a multiparameter model of thermal effluent jets and plumes, simulated annealing parameter estimation, and a multi-sensor indicator function. Using these tools, an adaptive multi-vehicle transect sampling behavior is implemented to efficiently sample an industrial jet. The capabilities of this behavior are demonstrated in realistic mission simulations and in field trials using a fleet of autonomous surface vehicles.