Autonomous marine vehicles (AMVs) are typically deployed for long periods of time in the ocean to monitor different physical, chemical, and biological processes. Given their limited
energy budgets, it makes sense to consider motion plans that leverage the dynamics of the surrounding flow field so as to minimize energy usage for these vehicles.  This project focuses on developing suitable graph search based techniques to compute energy and/or time optimal
paths for AMVs in two- and three-dimensional time-varying flows (2D+1 and 3D+1).   This project has contributed novel techniques that can capture the kinematic actuation
constraints on the vehicles in our cost functions, generate optimal paths in different homotopy classes, and employ an adaptive discretization scheme to construct the search graph.  Our current efforts are focused on how best to leverage coherent structure information into our strategies.
This work is a collaboration between Dr. Subhrajit Bhattacharya at Lehigh University.