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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,同时保护救援人员的安全,这些救援人员将至少在明年在华盛顿奥索附近的2014年SR530泥石流中工作,以修复现场和修复道路。这些航班还有助于提高斯蒂尔瓜米什河其他部分居民的安全。小型固定翼和旋翼无人机系统用于对泥石流和河流难以进入的区域进行纵向调查。8月和11月的调查,结合早期的即时响应飞行,捕捉了泥石流和河流随时间的演变状态,验证了河流和泥石流如何随季节变化的模型,完善了新的地质和水文模型,并预测了2015年春季继续发生滑坡和洪水的可能性,这些可能会影响到SR530的居民和其他部分。该研究为机器人和网络物理系统社区提供了在不受控制的天气条件下的小型无人机系统性能数据,为人机交互社区提供了来自不同机构的用户如何与机器人数据交互,并为大数据提供了数据集,以探索如何最好地存档、管理和可视化数据。该研究正在指导新型小型无人机系统的设计,以支持对情况进行快速或经济有效的地理空间重建的应用,例如应急响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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SCC-CIVIC-PG Track B: Community-Centric Pre-Disaster Mitigation with Unmanned Aerial and Marine Systems
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
Data-driven Recommendation System Construction of an Online Medical Platform Based on the Fusion of Information
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: