The Role of adaptive mission planning and control in persistent autonomous underwater vehicles presence

M. Brito, N. Bose, Ron Lewis, P. Alexander, G. Griffiths, J. Ferguson
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引用次数: 17

Abstract

The Autonomous Underwater Vehicle (AUV) community has for many years recognized the potential benefits made by adapting mission planning on-the-fly. Over the years there has been some degree of success in applying adaptive mission planning to very specific problems. Examples of applications include capabilities for a vehicle to search for, and then modify its trajectory to follow, a feature such as a plume or a thermocline, or to modify its trajectory to avoid an obstacle, or to find and follow a feature such as a pipeline. Despite an evident increase in the number of applications, the use of adaptive mission planning is still in its infancy. There is no doubt that adaptive mission planning will play a pivotal role in future AUV persistent presence. So what is delaying this technology from making the leap towards wider industry acceptance? This paper reviews the literature in adaptive mission planning and uses a failure analysis technique to identify key obstacles for the integration of this technique in wider AUV applications. We use our failure analysis to help devise recommendations for mitigating these obstacles. The complexity of the mathematical approaches used by adaptive techniques is one key obstacle. Perhaps of more importance is that the AUV community is increasingly requiring quantitative assessment of risk associated with the use of AUVs. We propose that probability is the appropriate measure for quantifying the risk of adaptive systems and their uncertainty. The work here presented is a collective endeavor of the Engineering Committee on Oceanic Resources Specialist Panel on Underwater Vehicles.
自适应任务规划与控制在水下航行器持续自主存在中的作用
多年来,自主水下航行器(AUV)社区已经认识到动态调整任务规划所带来的潜在好处。多年来,在将适应性任务规划应用于非常具体的问题方面取得了一定程度的成功。应用实例包括车辆搜索,然后修改其轨迹以跟随羽流或温跃层等特征,或修改其轨迹以避开障碍物,或发现并跟随管道等特征。尽管应用程序的数量明显增加,但自适应任务规划的使用仍处于初级阶段。毫无疑问,适应性任务规划将在未来的AUV持久存在中发挥关键作用。那么,是什么阻碍了这项技术向更广泛的行业接受迈进呢?本文回顾了自适应任务规划方面的文献,并使用失效分析技术来确定将该技术集成到更广泛的AUV应用中的关键障碍。我们使用故障分析来帮助设计减轻这些障碍的建议。自适应技术所使用的数学方法的复杂性是一个关键障碍。也许更重要的是,AUV社区越来越需要对AUV使用相关的风险进行定量评估。我们提出概率是量化自适应系统风险及其不确定性的适当度量。这里介绍的工作是海洋资源工程委员会水下航行器专家小组的集体努力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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