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NRI: Collaborative Research: Enabling Risk-Aware Decision Making in Human-Guided Unmanned Surface Vehicle Teams

NRI: Collaborative Research: Enabling Risk-Aware Decision Making in Human-Guided Unmanned Surface Vehicle Teams
NRI:协作研究:在人类引导的无人地面车辆团队中实现风险意识决策
批准号:
1634433
负责人:
Satyandra Gupta
金额:
$52.62万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-01-06 至 2019-08-31

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项目成果

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中文摘要
翻译
在过去的十年中,小型低成本无人水面车辆(usv)的发展取得了实质性进展。在许多民用应用中,部署由几个小型无人潜航器和一个或多个人类监督员组成的人机团队可以显着降低成本,提高安全性并提高操作效率。代表性应用包括远程/持久海洋传感,海上搜索和救援,拥挤港口环境中的海上作业,以及工业海上供应和支持。usv面临着室内机器人无法经历的独特挑战,例如:需要遵守海上导航规则(COLREGs);局部电流、波浪和风力条件会严重降低传感器和执行器的动态范围;频繁的通信中断;在户外水上作业中,由于情况瞬息万变,风险和紧迫性也随之增加。本研究旨在开发决策基础,使人类和usv团队能够执行复杂的协作任务。从监管和实践的角度来看,这一领域的进展对于USV系统的未来部署都是极其重要的。这项研究的结果将通过降低部署成本和民用应用中的操作风险,利用usv的巨大潜力。将研究与研究生及本科生课程相结合,将提升机器人及海洋工程课程,并丰富参与学生的学习经验。外展活动将教育和告知K-12学生有关海洋机器人的就业机会。所提议的努力的总体目标是在风险知情决策方面取得进展,以便usv团队和人类监督员能够在各种任务中合作。拟议的工作将通过利用任务协调和分配、计划、反应行为和控制方面的最新进展,开发一种全面的分布式决策方法,以实现在民用应用中部署人类制导的USV小组。将追求这些组成部分的进展,以确保它们彼此一致,并在决策过程中明确考虑风险。这项研究将开发团队任务模型的方法,以确保决策的所有阶段都有做出明智决策所需的信息。将开发决策方法,用于USV团队的稀疏咨询控制,以降低风险,并协调和分配团队中不同USV的任务。还将开发算法,用于风险意识审慎轨迹规划以及生成和执行反应性行为,以减轻风险。开发的方法将通过水上现场试验进行验证。
英文摘要
Over the last ten years, substantial progress has been made in the development of small low-cost unmanned surface vehicles (USVs). There are a number of civilian applications where deploying a human-robot team consisting of several small USVs and one or more human supervisors can significantly reduce costs, improve safety, and increase operational efficiencies. Representative applications include remote/persistent ocean sensing, marine search and rescue, maritime operations in congested port environments, and industrial offshore supply and support. USVs face unique challenges that are not experienced by robots operating indoors, such as: the need to adhere to marine navigation rules (COLREGs); local current, wave and wind conditions that can severely reduce the dynamic range of sensors and actuators; frequent communication interruptions; and risk and urgency due to rapidly changing situations during outdoor on-water operations. This research aims to develop decision making foundations for enabling teams of humans and USVs to perform complex collaborative tasks. Advances in this area could be extremely important from both a regulatory and practical standpoint for the future deployment of USV systems. Results from this research will enable leveraging the tremendous potential of USVs by reducing the cost of deployment and operational risks in civilian applications. The integration of the research with graduate and undergraduate courses will enhance the robotics and ocean engineering curricula and enrich learning experiences of the participating students. Outreach activities will educate and inform K-12 students about career opportunities in marine robotics. The overall goal of the proposed effort is to make advances in risk-informed decision making so that teams of USVs and human supervisors can work cooperatively on a wide variety of missions. The proposed work will develop a comprehensive distributed decision making approach by leveraging the latest advances in task coordination and assignment, planning, reactive behaviors, and control to enable the deployment of human-guided USV teams in civilian applications. Progress in these constituent components will be pursued to ensure that they are consistent with each other and to explicitly account for risk during decision making. This research will develop methodologies to model team missions to ensure that all phases of decision making will have the required information for making informed decisions. Decision making methodologies will be developed for sparse advisory control of USV teams to mitigate risks and for coordinating and assigning tasks to different USVs in the team. Algorithms will also be developed for risk-aware deliberative trajectory planning and generating and executing reactive behaviors for mitigating risks. The methods developed will be validated through on-water field experiments.
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  • 资助金额:
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  • 批准号:
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  • 项目类别:
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  • 资助金额:
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海外基金