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Time-Optimal Multi-Waypoint Mission Planning in Dynamic Environments

机译:动态环境中的时间最佳多路点任务规划

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The present paper demonstrates the use of exact equations to predict time-optimal mission plans for a marine vehicle that visits a number of locations in a given dynamic ocean current field. This problem bears close resemblance to that of the classic "traveling salesman", albeit with the added complexity that the vehicle experiences a dynamic flow field while traversing the paths. The paths, or "legs", between all goal waypoints are generated by numerically solving the exact time-optimal path planning level-set differential equations. Overall, the planning proceeds in four steps. First, current forecasts for the planning horizon is obtained utilizing our data-driven 4-D primitive equation ocean modeling system (Multidisciplinary Simulation Estimation and Assimilation System; MSEAS), forced by high-resolution tidal and real-time atmopsheric forcing fields. Second, all tour permutations are enumerated and the minimum number of times the time-optimal PDEs are to be solved is established. Third, due to the spatial and temporal dynamics, a varying start time results in different paths and durations for each leg and requires all permutations of travel to be calculated. To do so, the minimum required time-optimal PDEs are solved and the optimal travel time is computed for each leg of all enumerated tours. Finally, the tour permutation for which travel time is minimized is identified and the corresponding time-optimal paths are computed by solving the backtracking equation. Even though the method is very efficient and the optimal path can be computed serially in real-time for common naval operations, for additional computational speed, a high-performance computing cluster was used to solve the level set calculations in parallel. Our equation and software is applied to simulations of realistic naval applications in the complex Philippines Archipelago region. Our method calculates the global optimum and can serve two purposes: (a) it can be used in its present form to plan multi-waypoint missions offline in conjunction with a predictive ocean current modeling system, or (b) it can be used as a litmus test for approximate future solutions to the traveling salesman problem in dynamic flow fields.
机译:本文演示了使用确切方程来预测访问给定动态海洋电流场中许多位置的海运车辆的最佳任务计划。这一问题与经典的“旅行推销员”相比,尽管具有额外的复杂性,但是车辆在遍历路径时遇到动态流场的额外复杂性。通过在数值上求解确切的时间最佳路径规划级别设置差分方程,产生所有目标航路点之间的路径或“腿”。总体而言,规划在四个步骤中进行。首先,利用我们的数据驱动的4-D原始方程海洋建模系统(多学科仿真估计和同化系统; MSEAS)获得了对规划地平线的电流预测,由高分辨率潮汐和实时静止势在场迫使领域。其次,枚举所有旅游排列,并建立了要解决时间最佳PDE的最小次数。第三,由于空间和时间动态,不同的开始时间导致每个腿的不同路径和持续时间,并且需要计算行程的所有排列。为此,解决了最低所需的时间最佳PDE,并且针对所有枚举的旅游的每个腿计算最佳旅行时间。最后,确定了最小化行程时间的巡回栏,并且通过求解回溯方程来计算相应的时间最优路径。即使该方法非常有效,并且可以在常见的海军操作实时计算最佳路径,用于额外的计算速度,用于并行地解决高度性能计算群集来解决电平集计算。我们的公式和软件应用于复杂菲律宾群岛地区的现实海军应用的模拟。我们的方法计算全局最优,可以为两个目的服务:(a)它可以用其目前的形式使用,以便与预测的海洋电流建模系统一起使用多线点任务,或者(b)它可以用作Litmus测试动态流场中旅行推销员问题的近似未来解决方案。

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