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arXiv 2408.16624math.NAcs.NAmath.OC
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利用随机最优控制对反水雷模拟中的沙波纹进行建模

Modelling sand ripples in mine countermeasure simulations by means of stochastic optimal control

Philippe Blondeel, Filip Van Utterbeeck, Ben Lauwens

AI总结:

本文提出一种基于随机最优控制框架的新方法,用于在计算自主车辆轨迹时对海底沙波纹进行建模,以改善反水雷搜索任务中的水雷探测能力。

摘要:

对配备能在海上探测水雷传感器的自主车辆执行反水雷(MCM)搜索任务进行建模和模拟是一项具有挑战性的工作。在本研究中,我们提出了一种新方法,通过随机最优控制框架,在计算自主车辆的轨迹时对海底存在的沙波纹进行建模和考量。据科学文献所知,这些波纹会影响自主车辆对海水雷的探测能力。

英文摘要:

Modelling and simulating mine countermeasures (MCM) search missions performed by autonomous vehicles equipped with a sensor capable of detecting mines at sea is a challenging endeavour. In this work, we present a novel way to model and account for sand ripples present on the bottom of the ocean while calculating trajectories for the autonomous vehicles by means of a stochastic optimal control framework. It is known from the scientific literature that these ripples impact the sea mine detection capabilities of the autonomous vehicles.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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