RAPID: Using an Unmanned Aerial Vehicle and Increased Autonomy to Improve an Unmanned Marine Vehicle Lifeguard Assistant Robot
RAPID:使用无人驾驶飞行器和增强的自主性来改进无人驾驶海上飞行器救生员助理机器人
基本信息
- 批准号:1637214
- 负责人:
- 金额:$ 12.5万
- 依托单位:
- 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:2016-06-15 至 2017-05-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
NSF 1637214 RAPID: Using an Unmanned Aerial Vehicle and Increased Autonomy to Improve an Unmanned Marine Vehicle Lifeguard Assistant RobotThe United States is at risk for a mass marine casualty event, such as the Costa Concordia, or MV Sewol ferry sinking, but fortunately robots, such as the EMILY tele-operated unmanned marine surface vehicle (USV) can assist as mobile life preservers. EMILYs are now in use by the Hellenic Coast Guard and Red Cross throughout Greece. The responders have requested that EMILY navigate autonomously so that a lifeguard could designate a cluster of people in the water and then EMILY would autonomously drive to the victims in the water who would grab, hold, and wait while the human lifeguards focused on other people needing immediate assistance due to unconsciousness, risk of hypothermia (especially children), or high distress. Prof. Robin Murphy will engage 44 graduate and undergraduates in implementing an upgrade to EMILY so that it can use the view from a small tethered UAV combined with onboard thermal sensing to autonomously navigate to a cluster of people. The project will bring 11 of these US students to Greece for two field research expeditions to work with lifeguard teams actively responding to the shifting, but ongoing, patterns of boat refugees. The students will participate in two international workshops. The National Technical University of Athens (NTUA) is a partner in this research activity, and will be providing thermal imaging expertise. The project will introduce the students to participatory research with international collaborators in Greece, and train them to be technically competitive in an innovative, global workplace. It will potentially save lives in Greece and Europe, and ultimately contribute more effectively in search-and-rescue missions in the U.S. This 9-month project will involve 5 graduate students and 39 undergraduates in field robotics research. The students will address how to navigate and reach poses in waves and surf with a non-holonomic, under-actuated marine vehicle that cannot back up, has momentum, and a limited turning radius. They will employ known behavioral sensor fusion methods for reliable and efficient navigation targeting people using thermal imagery. They will collect data from the smart EMILY in the field with responders in uncontrolled weather and waves and make additional rounds of appropriate improvements and evaluation. Finally, the project will produce a longitudinal case study of how to work with users. The research will advance the theory of intelligent robotics-- especially interoperable and reliable computer systems, unmanned marine systems in shallow littoral operations, tethered unmanned aerial systems, heterogeneous teams, and human-robot interaction-- by implementing and field testing promising algorithms and known principles. The participating American students will be globally competitive, the data will give US companies a competitive edge, and the project will serve the use of autonomous systems in accordance with US and international regulations.This grant was funded by NSF Directorate of Computer & Information Science & Engineering (CISE), and Office of International Science and Engineering (OISE).
NSF 1637214快速:使用无人飞行器并增加自主权来提高无人驾驶的海洋救生员助理机器人机器人机器人,美国面临着大规模海洋伤亡事件的风险,例如Costa concordia,或MV Sewol渡轮,但诸如Emily Tele-Tele-Tele-Tele-Tele-Tele-Tele-Tele-Tele-Tele-Tele-tele-tele-tele-tele-tele-telemanned Marine Sporters willers(US Sporters Surpiers)的行动者(US)的行动者(US)的行动者(US)的危险。希腊海岸警卫队和整个希腊的红十字会正在使用艾米丽(Emilys)。响应者要求艾米丽(Emily)自主行驶,以便救生员可以指定水中的一群人,然后艾米丽(Emily)自主开车去水中的受害者,他们会抓住,抓住和等待的人,而人类救生员则专注于其他需要立即援助的人,因为无意识的风险,尤其是儿童的风险(尤其是儿童),或者是痛苦的。罗宾·墨菲(Robin Murphy)教授将与44名毕业生和本科生一起实施艾米丽(Emily)的升级,以便它可以使用来自小的束缚无人机的视图,并结合板上的热传感,自动导航到一群人。该项目将将其中11名美国学生带到希腊进行两次实地研究探险,与救生员团队一起工作,积极回应船只难民的迁移,但持续的模式。学生将参加两个国际研讨会。雅典国家技术大学(NTUA)是这项研究活动的合作伙伴,将提供热成像专业知识。该项目将向学生介绍与希腊国际合作者的参与性研究,并培训他们在创新的全球工作场所具有技术竞争力。它可能会挽救希腊和欧洲的生命,并最终在美国的搜索和救援任务中做出更有效的贡献,这个9个月的项目将涉及5名研究生和39名本科生在Field Robotics Research中。学生们将用一辆无法备份,动力和有限的转弯半径来解决如何在海浪中导航和伸出姿势。他们将采用已知的行为传感器融合方法,用于使用热图像的可靠,有效的导航对象。他们将在不受控制的天气和波浪中与响应者在现场的Smart Emily中收集数据,并进行其他适当的改进和评估。最后,该项目将对如何与用户合作进行纵向案例研究。这项研究将通过实施和现场测试有希望的算法和已知原理来推进智能机器人技术的理论,尤其是互操作和可靠的计算机系统,无人驾驶的海洋系统,无人驾驶的空中系统,异质团队和人类机器人的交互。参与的美国学生将具有全球竞争性,数据将为我们的公司带来竞争优势,该项目将根据美国和国际法规服务于自治系统。该赠款由NSF计算机与信息科学与工程局(CISE)以及国际科学与工程办公室(OISE)资助。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Robin Murphy其他文献
Smart film actuators using biomass plastic
使用生物质塑料的智能薄膜执行器
- DOI:
- 发表时间:
2011 - 期刊:
- 影响因子:4.1
- 作者:
Satoshi Tadokoro;Robin Murphy;Samuel Stover;William Brack;Masashi Konyo;Toshihiko Nishimura;Osachika Tanimoto;米山聡,田中信雄 - 通讯作者:
米山聡,田中信雄
Preliminary Observation of HRI in Robot-Assisted Medical Response
HRI 在机器人辅助医疗救治中的初步观察
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Robin Murphy;Masashi Konyo;Satoshi Tadokoro;Pedro Davalas;Gabe Knezke;Maarten Van Zomeren - 通讯作者:
Maarten Van Zomeren
Application of Active Scope Camera to Forensic Investigation of Construction Accident
主动式摄像头在建筑事故法医学调查中的应用
- DOI:
- 发表时间:
2009 - 期刊:
- 影响因子:0
- 作者:
Satoshi Tadokoro;Robin Murphy;Samuel Stover;William Brack;Masashi Konyo;Toshihiko Nishimura;Osachika Tanimoto - 通讯作者:
Osachika Tanimoto
Robin Murphy的其他文献
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{{ truncateString('Robin Murphy', 18)}}的其他基金
RAPID/Collaborative Research: Datasets for Uncrewed Aerial System (UAS) and Remote Responder Performance from Hurricane Ian
RAPID/协作研究:飓风伊恩无人飞行系统 (UAS) 和远程响应器性能的数据集
- 批准号:
2306453 - 财政年份:2023
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
SCC-CIVIC-PG Track B: Community-Centric Pre-Disaster Mitigation with Unmanned Aerial and Marine Systems
SCC-CIVIC-PG 轨道 B:利用无人机和海洋系统进行以社区为中心的灾前减灾
- 批准号:
2043710 - 财政年份:2021
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
EAGER: Evidence-Based Model of Adoption of Robotics for Pandemics and Natural Disasters
EAGER:采用机器人技术应对流行病和自然灾害的循证模型
- 批准号:
2125988 - 财政年份:2021
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
RAPID/Collaborative Research: Data Collection for Robot-Oriented Disaster Site Modeling at Champlain Towers South Collapse
快速/协作研究:尚普兰塔南倒塌的面向机器人的灾难现场建模数据收集
- 批准号:
2140451 - 财政年份:2021
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
SCC-CIVIC-FA Track B: Community-Centric Pre-Disaster Mitigation with Unmanned Aerial and Marine Systems
SCC-CIVIC-FA 轨道 B:利用无人机和海洋系统进行以社区为中心的灾前减灾
- 批准号:
2133297 - 财政年份:2021
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
EAGER: Documenting and Analyzing Use of Robots for COVID-19
EAGER:记录和分析机器人在 COVID-19 中的使用情况
- 批准号:
2032729 - 财政年份:2020
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
Best Viewpoints for External Robots or Sensors Assisting Other Robots
外部机器人或传感器协助其他机器人的最佳视角
- 批准号:
1945105 - 财政年份:2019
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
RAPID: Collaborative Research: Machine Learning for Dehazing Unmanned Aerial System Imagery from Volcanic Eruptions
RAPID:协作研究:用于消除火山喷发无人机系统图像雾霾的机器学习
- 批准号:
1840873 - 财政年份:2018
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
RAPID: Collaborative Research: Unmanned Aerial System Datasets from Hurricanes Harvey and Irma
RAPID:协作研究:飓风哈维和艾尔玛的无人机系统数据集
- 批准号:
1762137 - 财政年份:2017
- 资助金额:
$ 12.5万 - 项目类别:
Standard Grant
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