Path planning in uncertain flow fields using ensemble method
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- 作者：Tong Wang ; Olivier P. Le Maître ; Ibrahim Hoteit ; Omar M. Knio
- 关键词：Optimal path planning ; Heading control ; Ensemble forecast ; Polynomial chaos
- 刊名：Ocean Dynamics
- 出版年：2016
- 出版时间：October 2016
- 年：2016
- 卷：66
- 期：10
- 页码：1231-1251
- 全文大小：4,912 KB
- 刊物类别：Earth and Environmental Science
- 刊物主题：Earth sciences
Oceanography
Geophysics and Geodesy
Meteorology and Climatology
Fluids
Structural Foundations and Hydraulic Engineering - 出版者：Springer Berlin / Heidelberg
- ISSN：1616-7228
- 卷排序：66
文摘
An ensemble-based approach is developed to conduct optimal path planning in unsteady ocean currents under uncertainty. We focus our attention on two-dimensional steady and unsteady uncertain flows, and adopt a sampling methodology that is well suited to operational forecasts, where an ensemble of deterministic predictions is used to model and quantify uncertainty. In an operational setting, much about dynamics, topography, and forcing of the ocean environment is uncertain. To address this uncertainty, the flow field is parametrized using a finite number of independent canonical random variables with known densities, and the ensemble is generated by sampling these variables. For each of the resulting realizations of the uncertain current field, we predict the path that minimizes the travel time by solving a boundary value problem (BVP), based on the Pontryagin maximum principle. A family of backward-in-time trajectories starting at the end position is used to generate suitable initial values for the BVP solver. This allows us to examine and analyze the performance of the sampling strategy and to develop insight into extensions dealing with general circulation ocean models. In particular, the ensemble method enables us to perform a statistical analysis of travel times and consequently develop a path planning approach that accounts for these statistics. The proposed methodology is tested for a number of scenarios. We first validate our algorithms by reproducing simple canonical solutions, and then demonstrate our approach in more complex flow fields, including idealized, steady and unsteady double-gyre flows.