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RAPID: Data collection and curation of SR-530 mudslide with small unmanned aerial vehicles

RAPID: Data collection and curation of SR-530 mudslide with small unmanned aerial vehicles
RAPID:使用小型无人机收集和整理 SR-530 泥石流数据
批准号:
1445936
负责人:
Robin Murphy
金额:
$4.2万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-08-01 至 2015-07-31

项目摘要

项目成果

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中文摘要
翻译
该项目对小型无人机系统进行研究,同时保护恢复工作人员的安全,这些工作人员将在2014年华盛顿州奥索附近的SR530泥石流中工作至少一年,以补救现场和修复道路。这些航班还有助于提高斯蒂拉瓜米什河其他部分沿线居民的安全。使用小型固定翼和旋翼机无人机系统对泥石流和河流难以到达的区域进行纵向勘测。8月和11月的调查,结合早期应急期间的飞行,捕捉泥石流和河流随时间的演变状态,验证河流和泥石流预计将如何随季节变化的模型,改进新的地质和水文模型,并预测2015年春季持续崩塌和洪水的可能性,这将影响SR530的居民和其他路段。这项研究正在为机器人和网络物理系统社区提供小型无人驾驶航空系统在不受控制的天气条件下的性能数据,为人机交互社区提供来自不同机构的用户如何与机器人数据交互,以及为大数据提供数据集,以探索如何随着时间的推移最好地归档、管理和可视化数据。这项研究正在指导新的小型无人驾驶航空系统的设计,以支持对局势进行快速或具有成本效益的地理空间重建的重要应用,如紧急反应和关键基础设施检查。
英文摘要
This project conducts research on small unmanned aerial systems while protecting the safety of recovery workers who will be working at the 2014 SR530 mudslide near Oso, Washington, for at least the next year to remediate the site and repair the road. The flights also help increase the safety of residents along other portions of the Stillaguamish River. A small fixed-wing and a rotorcraft unmanned aerial system are used to conduct longitudinal surveys of the inaccessible region of the mudslide and river. The surveys in August and November, combined with earlier flights during the immediate response, capture the evolving state of the mudslide and river over time, validate the models of how the river and mudslide are expected to change over the seasons, refine new geological and hydrological models, and predict the potential for continuing sloughing and flooding that will impact residents and other sections of SR530 in the spring of 2015. The research is providing the robotics and cyber-physical systems communities with small unmanned aerial systems performance data under uncontrolled weather conditions, the human-robot interaction community with how users from different agencies interact with the robot data, and Big Data with datasets to explore how to best archive, curate, and visualize data over time. The research is guiding the design of new small unmanned aerial systems to support applications where rapid or cost-effective geospatial reconstruction of the situation is important, such as emergency response and critical infrastructure inspection.
期刊论文(0)
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会议论文
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EAGER: Evidence-Based Model of Adoption of Robotics for Pandemics and Natural Disasters
RAPID/Collaborative Research: Data Collection for Robot-Oriented Disaster Site Modeling at Champlain Towers South Collapse
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
  • 批准号:
    --
  • 项目类别:
    --
  • 资助金额:
    40万元
  • 批准年份:
    2020
  • 负责人:
    Vikrant Gupta
  • 依托单位:
基于Linked Open Data的Web服务语义互操作关键技术
  • 批准号:
    61373035
  • 项目类别:
    面上项目
  • 资助金额:
    77.0万元
  • 批准年份:
    2013
  • 负责人:
    冯志勇
  • 依托单位: