Trajectory Optimization for Underwater Vehicles in Time-Varying Ocean Flows

Aguiar, Miguel; Sousa, João Borges de; Dias, João Miguel; Silva, Jorge Estrela da; Mendes, Renato; Ribeiro, Américo S.

doi:10.1109/auv.2018.8729777

Cited by 4 publications

(2 citation statements)

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“…The data used for these examples was produced by a high resolution model of the area of the Sado river estuary in September 2018. For a detailed description of the model used to generate the data, see our previous paper [11] or Ribeiro et al [10]. The values of the ocean current velocity are defined on a spatially curvilinear grid with a mean resolution of 100 meters, with a temporal sampling rate of 10 minutes.…”

Section: Numerical Examplesmentioning

confidence: 99%

“…Numerical methods for dynamic programming, however, typically suffer from the socalled 'curse of dimensionality', meaning that the complexity increases significantly with the increase in the number of dimensions. In a previous paper [11] we reported large computation times (approx. 5 hours) for a realistic benchmark problem, using a MATLAB software package.…”

Section: Introductionmentioning

confidence: 95%

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Optimizing autonomous underwater vehicle routes with the aid of high resolution ocean models

Aguiar

Sousa

Dias

et al. 2019

Oceans 2019 MTS/Ieee Seattle

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In underwater vehicle operations in areas such as estuaries, vehicles may face currents with magnitudes equal to or exceeding the vehicle's maximum forward speed. We propose a method which generates vehicle routes taking into account ocean current forecasts from high resolution ocean models, in order to both take advantage of the ocean current velocity and avoid its negative effects. We formulate the problem in an optimal control setting and derive the associated Hamilton-Jacobi-Bellman partial differential equation (PDE). We solve this PDE using a parallelized C++ implementation of a numerical method which allows us to obtain the solution in a few minutes on a mainstream computer. After obtaining the solution of the PDE, optimal trajectories with any initial condition can be computed efficiently. The method is illustrated using data from highresolution ocean models of the Sado river estuary in Portugal. Two mission scenarios are analyzed, which highlight the influence of ocean currents on optimal trajectories and the benefits of considering ocean current forecasts in mission planning.

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Section: Numerical Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%