Robotic simulation of dynamic plume tracking by Unmanned Surface Vessels

Abstract

Using autonomous mobile robots to dynamically track oil plume propagation in ocean environments is challenging. Based on a model of advection-diffusion equation that describes point-source pollution propagation in marine environments, we have previously proposed a model-based estimator-controller design for autonomous robots to dynamically track plume front propagation. In this paper we study the robustness of the controller in a robot simulator, and evaluate it's performance in a realistic environmental model setup. A probabilistic Lagrangian environmental model is used that can capture both the time-averaged, idealized structure and the instantaneous, realistic structure of a dynamic plume. The controller is implemented on the Field Robotics Lab Vehicle Software, which uses Lightweight Communication and Marshalling library to facilitate process communication and for easy transit to field testing. Simulation results are shown with discussions and lessons learned to guide future field experiments.