Ocean Plume Tracking with Unmanned Surface Vessels: Algorithms and Experiments
This addresses pollution monitoring for environmental protection, but it is incremental as it builds on existing plume models and autonomous vehicle control methods.
The paper tackled the problem of autonomously tracking pollution plumes in marine environments using unmanned surface vessels, presenting a control law based on an advection-diffusion model and field experiments with Rhodamine dye, achieving successful autonomous tracking in real-world conditions.
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.