Elsevier

Ocean Modelling

Volume 94, October 2015, Pages 46-66
Ocean Modelling

Path planning in multi-scale ocean flows: Coordination and dynamic obstacles

https://doi.org/10.1016/j.ocemod.2015.07.013Get rights and content

Highlights

  • Derived level-set methodology for distance-based coordination of multiple vehicles operating in minimum time in ocean flows.

  • Ocean currents, short-term reachability sets, and optimal headings are predicted for dynamic formation control.

  • Obtained an efficient, non-intrusive technique for level-set-based time-optimal path planning within moving obstacles.

  • Time-optimal paths that avoid moving obstacles and sustain the desired coordination are exemplified for varied ocean flows.

  • Results are analyzed for the complex Philippine Archipelago, using data assimilative two-way nested reanalyses of currents.

Abstract

As the concurrent use of multiple autonomous vehicles in ocean missions grows, systematic control for their coordinated operation is becoming a necessity. Many ocean vehicles, especially those used in longer-range missions, possess limited operating speeds and are thus sensitive to ocean currents. Yet, the effect of currents on their trajectories is ignored by many coordination techniques. To address this issue, we first derive a rigorous level-set methodology for distance-based coordination of vehicles operating in minimum time within strong and dynamic ocean currents. The new methodology integrates ocean modeling, time-optimal level-sets and optimization schemes to predict the ocean currents, the short-term reachability sets, and the optimal headings for the desired coordination. Schemes are developed for dynamic formation control, where multiple vehicles achieve and maintain a given geometric pattern as they carry out their missions. To do so, a new score function that is suitable for regular polygon formations is obtained. Secondly, we obtain an efficient, non-intrusive technique for level-set-based time-optimal path planning in the presence of moving obstacles. The results are time-optimal path forecasts that rigorously avoid moving obstacles and sustain the desired coordination. They are exemplified and investigated for a variety of simulated ocean flows. A wind-driven double-gyre flow is used to study time-optimal dynamic formation control. Currents exiting an idealized strait or estuary are employed to explore dynamic obstacle avoidance. Finally, results are analyzed for the complex geometry and multi-scale ocean flows of the Philippine Archipelago.

Section snippets

Introduction and motivation

The simultaneous use of multiple agents enables complex tasks to be completed in a coordinated and robust manner. In nature, coordination is commonly exhibited by bees, birds, ants, and other animals when they perform activities such as foraging, navigation and hunting. Coordination also improves the overall performance of teams of autonomous robots. Multi-agent systems are then also versatile and effective in completing tasks such as exploring, mapping and monitoring. To execute such tasks,

Time-optimal path planning using level-set equations

Our results on time-optimal navigation in dynamic ocean flows with moving obstacles and time-optimal coordinated formation control are based on a recent level-set approach (Lolla, Haley, Lermusiaux, 2014a, Lolla, Lermusiaux, Ueckermann, Haley, 2014b, Lolla, Ueckermann, Yigit, Haley Jr., Lermusiaux, 2012). These level-set equations, which can be directly solved for in ocean models, are now outlined. The presentation is limited to two dimensions; the extension to higher dimensions is

Time-optimal path planning in the presence of dynamic obstacles

The methodology for time-optimal path planning (Section 2) is now extended to handle moving obstacles and forbidden regions, without any increase in the computational cost. Unlike solid obstacles, forbidden regions (e.g. fishing zones, polluted areas, regulated territories) do not affect the flow-field. It is only the AUVs that cannot operate in such regions. Henceforth, both these types of impediments will usually be simply referred to as obstacles. Our objective then is to rigorously compute

Coordination of underwater vehicles using level-set methods

We now derive a rigorous methodology for distance-based coordination of AUVs operating in minimum-time, within strong and dynamic flows. To do so, we integrate a leader–follower coordination technique with ocean predictions and the above level-set approach (Section 2). The goal is to enable safe, coordinated motion of vehicles in dynamic currents, where the coordination constraints are formulated in the form of relative positions of the vehicles or inter-vehicle spacing during the mission. The

Applications

In what follows, we exemplify our schemes for dynamic formation control and path planning with dynamic obstacles, and analyze their respective results, using several ocean flows. We first consider time-optimal coordinated vehicle motion within an idealized wind-driven double-gyre (Section 5.1). We then demonstrate time-optimal path planning in the presence of moving obstacles within currents exiting an idealized strait or estuary (Section 5.2). Finally, we analyze the results of time-optimal

Summary and conclusions

For many ocean applications, the coordinated operation of multiple AUVs provides significant advantages such as robustness and efficiency, thereby enhancing the utility of individual vehicles. Most coordination techniques usefully assume that the kinematics of vehicles are unaffected by the benign environment in which they operate. However, in the ocean, longer-range underwater vehicles, especially gliders, possess limited relative operating speeds. It is thus important to account for the

Acknowledgments

We acknowledge the Office of Naval Research for supporting this research under grants N00014-09-1-0676 (Science of Autonomy, A-MISSION), N00014-14-1-0476 (LEARNS), N00014-07-1-0473 (PhilEx) and N00014-12-1-0944 (ONR6.2) to the Massachusetts Institute of Technology (MIT). We are thankful to the members of the MSEAS group and to the PhilEx team for several helpful discussions. We also thank the anonymous reviewers for their useful comments.

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