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Time-Optimal Path Planning: Real-Time Sea Exercises

机译:最优路径规划:实时海锻炼

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We report the results of sea exercises that demonstrate the real-time capabilities of our fundamental time-optimal path planning theory and software with real ocean vehicles. The exercises were conducted with REMUS 600 Autonomous Underwater Vehicles (AUVs) in the Buzzards Bay and Vineyard Sound Regions on 21 October and 6 December 2016. Two tests were completed: (i) 1-AUV time-optimal tests and (ii) 2-AUV race tests where one AUV followed a time-optimal path and the other a shortest-distance path between the start and finish locations. The time-optimal planning proceeded as follows. We first forecast, in real-time, the physical ocean conditions in the above regions and times utilizing our MSEAS multi-resolution primitive equation ocean modeling system. Next, we planned time-optimal paths for the AUVs using our level-set equations and real-time ocean forecasts, and accounting for operational constraints (e.g. minimum depth). This completed the planning computations performed onboard a research vessel. The forecast optimal paths were then transferred to the AUV operating system and the vehicles were piloted according to the plan. We found that the forecast currents and paths were accurate. In particular, the time-optimal vehicles won the races, even though the local currents and geometric constraints were complex. The details of the results were analyzed off-line after the sea tests.
机译:我们报告了海洋练习的结果,证明了我们基本上最优路径规划理论和具有真正海洋车辆的软件的实时能力。在2016年10月21日和6月6日,在Buzzards Bay和Vineyard Sound地区的雷姆斯600自主水下车(AUV)进行了锻炼。两次测试完成了:(i)1-AUV时间最佳测试和(ii)2- AUV竞争测试,其中一个AUV遵循时间最佳路径,并且在开始和完成位置之间的另一个最短距离路径。时间最佳规划如下进行。我们首先预测上述地区的物理海洋状况和时代利用我们的MSEA多分辨率原始方程海洋建模系统。接下来,我们使用我们的级别设置方程和实时海洋预测的AUV计划的时间最佳路径,以及用于操作约束(例如最小深度)。这完成了计划计算的计划计算船只。然后将预测的最佳路径转移到AUV操作系统,并且根据该计划试驾车辆。我们发现预测电流和路径准确。特别是,即使局部电流和几何限制是复杂的,时间最佳车辆赢得了比赛。在海上测试后,结果分析了结果的细节。

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