Ocean Plume Tracking with Unmanned Surface Vessels: Algorithms and Experiments

TL;DR

This paper develops and tests algorithms for autonomous unmanned surface vessels to track pollution plumes in marine environments using concentration measurements and field experiments.

Contribution

It introduces a control law and gradient estimation method for plume tracking based solely on concentration data, validated through real-world experiments.

Findings

Successful autonomous plume tracking in field tests

Effective gradient estimation from concentration measurements

Insights into real-world marine environment complexities

Abstract

Pollution plume monitoring using autonomous vehicles is important due to the adverse effect of pollution plumes on the environment and associated monetary losses. Using the advection-diffusion plume dispersion model, we present a control law design to track dynamic concentration level curves. We also present a gradient and divergence estimation method to enable this control law from concentration measurement only. We then present the field testing results of the control law to track concentration level curves in a plume generated using Rhodamine dye as a pollution surrogate in a near-shore marine environment. These plumes are then autonomously tracked using an unmanned surface vessel equipped with fluorometer sensors. Field experimental results are shown to evaluate the performance of the controller, and complexities of field experiments in real-world marine environments are discussed in the paper.