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NRI: Coordinated Detection and Tracking of Hazardous Agents with Aerial and Aquatic Robots to Inform Emergency Responders

NRI：与空中和水上机器人协调检测和跟踪危险物质，以通知紧急救援人员

基本信息

批准号：
1637915
负责人：
Ryan Williams
金额：
$ 90.08万
依托单位：
Virginia Polytechnic Institute and State University
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
起止时间：
2016-10-01 至 2020-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1637915&HistoricalAwards=false
关键词：
NRI Coordinated Detection Tracking Hazardous

项目摘要

New tools and technology are needed to rapidly assess hazardous agents in the environment and inform emergency responders. Unmanned surface vehicles (USVs) have been used to monitor pollutant plumes in aquatic environments. However, USVs can only provide a close-up view of the plumes. Unmanned aerial systems (UASs) can survey large areas, but only from a distance. This project addresses the challenges in tracking flows of pollutants using a team of UASs and USVs. UASs are used as scouts to direct USVs to efficiently sample the water for testing. The results will provide emergency responders with technology that can provide rapid, actionable information on the dispersal of hazardous agents. This technology will be of immediate value in the development of early-warning systems for airborne hazards such as chemicals and radioactive particles. In an effort to encourage careers in robotics and emergency response, this project delivers a unique interdisciplinary robotics unit for 75 high school students. Efficient coordination algorithms are required to fully exploit heterogeneity in sensing of teams of autonomous surface and aerial vehicles. When moving through the water, a plume of hazardous agents may bifurcate into different flow regimes, complicating the sampling and control scenario. This project: (1) develops approximation algorithms for multi-resolution, informative trajectory planning to track spatio-temporal plumes with UAS teams; (2) develops an autonomous USV to sample and characterize a surrogate hazardous agent in the water and air; (3) conducts field sampling campaigns with emergency responders (Virginia Tech Rescue Squad, a unique group of stakeholders consisting of 50 student members) to find and localize sources of a surrogate hazardous agent; and (4) develops a unique interdisciplinary robotics unit for 75 high school students representing a range of ages, ethnicities, and socioeconomic classes.

需要新的工具和技术来快速评估环境中的危险物质并通知应急人员。无人水面飞行器(USV)已被用于监测水环境中的污染物羽流。然而，无人潜航器只能提供羽流的近距离观察。无人驾驶航空系统(UAS)可以探测大片区域，但只能从很远的地方进行。该项目解决了使用UAS和USV团队跟踪污染物流动方面的挑战。UAS被用作侦察员，指导USV有效地对水进行采样以进行测试。这一结果将为应急人员提供技术，提供有关危险物质扩散的快速、可操作的信息。这项技术将对开发化学物质和放射性粒子等空气传播危险的早期预警系统具有直接价值。为了鼓励在机器人和紧急反应领域的职业，该项目为75名高中生提供了一个独特的跨学科机器人单元。需要高效的协调算法来充分利用自主地面和飞行器团队的异构性。当在水中移动时，一股有害物质可能会分叉成不同的流态，使采样和控制情况变得复杂。该项目：(1)与UAS团队一起开发多分辨率、信息丰富的轨迹规划的近似算法，以跟踪时空羽流；(2)开发自主USV，以对水和空气中的替代危险物质进行采样和表征；(3)与应急人员(弗吉尼亚理工大学救援队，由50名学生组成的独特利益攸关方小组)开展现场采样活动，以发现并定位替代危险物质的来源；以及(4)为75名高中生开发一个独特的跨学科机器人单元，代表不同年龄、种族和社会经济阶层。

项目成果

期刊论文数量（12）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Algorithm for searching and tracking an unknown and varying number of mobile targets using a limited FoV sensor

使用有限 FoV 传感器搜索和跟踪未知且变化数量的移动目标的算法

DOI：
10.1109/icra.2017.7989740
发表时间：
2017
期刊：
Proceedings of the IEEE International Conference on Robotics and Automation (ICRA
影响因子：
0
作者：
Sung, Yoonchang;Tokekar, Pratap
通讯作者：
Tokekar, Pratap

Resilient Active Target Tracking With Multiple Robots