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首页> 外文期刊>IEEE Transactions on Engineering Management >Adaptive Autonomous Underwater Vehicles: An Assessment of Their Effectiveness for Oceanographic Applications
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Adaptive Autonomous Underwater Vehicles: An Assessment of Their Effectiveness for Oceanographic Applications

机译：自适应自主水下航行器：对海洋学应用有效性的评估

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摘要

Autonomous underwater vehicles (AUVs) are practical tools for ocean observation. However, they tend to operate in an automatic rather than autonomous way. This reflects the attitudes and behaviors that individuals and organizations share when adopting new technology in this industry. This paper clarifies the factors that are preventing one important aspect of autonomy-adaptive mission planning (AMP)-from transitioning from research to commercial and bespoke AUVs. A total of 25 experts comprising AUV developers and users, with combined 237 years of experience, provided their views in a structured survey covering several different hypotheses. There is insufficient evidence to determine clearly a single reason for failure to adopt AMPs, but a primary cause is the paucity of demonstration trials. This view is irrespective of participants' years of experience. Managers, engineers, and technologists agree on the two most likely causes for failure to adopt AMPs. However, the differences between the assessments provided by researchers and these three professional groups are statistically significant, with p value <0.005. For researchers, complexity is one of the two most important inhibitory factors. We present recommendations to support the integration of AMP into AUVs substantiated by recent examples where government, industry, and researchers have developed and tested AMPs.
机译：自主水下航行器（AUV）是用于海洋观测的实用工具。但是，它们倾向于以自动而不是自主的方式运行。这反映了个人和组织在行业中采用新技术时所共享的态度和行为。本文阐明了阻碍自主自适应任务计划（AMP）的一个重要方面-从研究过渡到商业和定制AUV的因素。由AUV开发人员和用户组成的总共25位专家，结合237年的经验，在涵盖几种不同假设的结构化调查中提供了他们的观点。没有足够的证据清楚地确定未能采用AMP的单一原因，但主要原因是缺乏示范试验。这种观点与参与者的多年经验无关。经理，工程师和技术人员就无法采用AMP的两个最可能的原因达成了共识。但是，研究人员与这三个专业组提供的评估之间的差异具有统计学意义，p值<0.005。对于研究人员而言，复杂性是两个最重要的抑制因素之一。我们提出了一些建议，以支持将AMP集成到AUV中，并在政府，行业和研究人员开发和测试AMP的最新实例中证实了这一点。

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