Planning the Minimum Time and Optimal Survey Trajectory for Autonomous Underwater Vehicles in Uncertain Current

The authors develop an approach to a “best” time path for Autonomous Underwater Vehicles conducting oceanographic measurements under uncertain current flows. The numerical optimization tool DIDO is used to compute hybrid minimum time and optimal survey paths for a sample of currents between ebb and flow. A simulated meta-experiment is performed where the vehicle traverses the resulting paths under different current strengths per run. The fastest elapsed time emerges from a payoff table. A multi-objective function is then used to weigh the time to complete a mission versus measurement inaccuracy due to deviation from the desired survey path.