Optimal Path Planning in Time-Varying Flows with Forecasting Uncertainties
Optimal Path Planning in Time-Varying Flows with Forecasting Uncertainties
复制标题
具有预测不确定性的时变流中的最优路径规划
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
M. A. Hsieh
中科院分区：
文献类型：
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作者：
D. Kularatne;Hadi Hajieghrary;M. A. Hsieh
为了在海洋环境中进行有效的路径规划，必须明确考虑流动模型中的不确定性。在本文中，我们提出了两种方法来计算不确定流模型上的最小期望成本策略和路径。第一种方法基于马尔可夫决策过程，计算最小期望代价策略，而第二种方法基于图搜索，计算最小期望代价路径。建立了一个转移概率模型来计算在给定作用下从一种状态转移到另一种状态的概率。此外，还给出了路径在不确定流场中执行时期望成本的计算方法。用这两种方法计算了海洋环境中的最小能量路径，并对结果进行了仿真分析。
Uncertainties in flow models have to be explicitly considered for effective path planning in marine environments. In this paper, we present two methods to compute minimum expected cost policies and paths over an uncertain flow model. The first method based on a Markov Decision Process computes a minimum expected cost policy while the second graph search based method, computes a minimum expected cost path. A transition probability model is developed to compute the probability of transition from one state to another under a given action. In addition, a method to compute the expected cost of a path when it is executed in an uncertain flow field is also presented. The two methods are used to compute minimum energy paths in an ocean environment and the results are analyzed in simulations.