IUCRC Phase I Virginia Tech: Center for Autonomous Air Mobility and Sensing (CAAMS)
IUCRC Phase I Virginia Tech: Center for Autonomous Air Mobility and Sensing (CAAMS)
批准号:
2137159
负责人:
Kevin Kochersberger
金额:
$46.77万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-04-15 至 2027-06-30
中文摘要
世界航空业正在走向自主空中机动性和传感,人工智能、能源系统、空气动力学、结构和材料、先进制造和多学科设计方面的新发展正在使新的飞行器概念和使用航空在日常信息、人员和货物运输中的新方式成为可能。自主空气移动和传感中心(CAAMS)将产生新的基础工程知识,开发新技术,并将通过将美国领先的工程研究大学的技术知识与从初创公司到航空航天行业历史悠久的领先企业的创新公司汇集在一起,培养所需的新劳动力。CAAMS的研究重点是通过将控制、空气动力学、结构和材料、通信和能量储存等传统航空领域的研究与人工智能、机器学习和机器人等新学科相结合,提高飞行器的性能、可持续性、安全系统、可制造性和可靠性。弗吉尼亚理工大学拥有美国联邦航空局指定的六个无人机试验场之一(中大西洋航空伙伴关系),该试验场支持在国家空域运行的飞行器系统的安全开发和批准。一个校园内的网络设施和一个4平方公里的带跑道的校外试验场(肯特兰农场)为CAAMS的研究人员提供了对交付研究成果至关重要的测试和评估能力。自主空中机动性和传感包括广泛的车辆概念、集成的子系统、支持基础设施、交通管理工具,以及利用航空领域日益自主的能力的应用程序。这些自主系统有可能提高安全性和可靠性,降低成本,并使具有国家和全球重要性的新任务成为可能。到2040年,全球自动驾驶飞机市场预计将达到1.5万亿美元,CAAMS将成为增强美国竞争力的关键资产。中心研究每年将支持数十名学生,让他们亲身体验先进的自主系统,并直接了解行业的观点和需求。中心的成果将通过档案出版物、在工程和计算机科学会议上的演讲以及与航空业成员的技术交流来广泛传播。销售线索站点将建立一个单一的中心范围的数据存储库,其中包含一个受密码保护的门户网站,所有中心行业成员都可以访问该门户。项目数据将每年向中心成员提供,并将在中心财政年度结束后两年应请求向公众提供。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The world’s aviation industry is moving towards autonomous air mobility and sensing, where new developments in artificial intelligence, energy systems, aerodynamics, structures and materials, advanced manufacturing, and multidisciplinary design are enabling new air vehicle concepts and new ways of using aviation in the daily transport of information, people, and cargo. The Center for Autonomous Air Mobility and Sensing (CAAMS) will produce new fundamental engineering knowledge, will develop new technologies, and will train a new workforce needed by pooling the technical know-how of America’s leading engineering research universities with innovative companies ranging from startups to long-established leaders in the aerospace industry.CAAMS research focuses on improving air vehicle performance, sustainability, safety systems, manufacturability, and reliability by integrating research in traditional aerospace fields such as control, aerodynamics, structures and materials, communication, and energy storage with new disciplines including artificial intelligence, machine learning, and robotics. Virginia Tech hosts one of six FAA-designated UAS test sites (the Mid-Atlantic Aviation Partnership) that supports the safe development and approval of air vehicle systems operating in the national airspace. An on-campus netted facility and a 4-km2 off-campus test site (Kentland Farm) with runway gives CAAMS researchers a test and evaluation capability critical to delivering results from research.Autonomous air mobility and sensing includes a broad range of vehicle concepts, integrated subsystems, supporting infrastructure, traffic management tools, and applications that exploit increasingly autonomous capabilities in aviation. These autonomous systems have the potential to improve safety and reliability, reduce costs, and enable new missions of national and global importance. The global market for autonomous aircraft is expected to reach $1.5 trillion by 2040, and CAAMS will be a key asset in enhancing US competitiveness. Center research will support dozens of students every year, giving them hands-on experience with advanced autonomous systems and direct understanding of industry perspectives and needs.Center outcomes will be broadly disseminated through archival publications, presentations at engineering and computer science conferences, and technical interchanges with aviation industry members. A single center-wide data repository will be established by the lead site with a password-protected web portal that can be accessed by all center industry members. Project data will be made available to center members annually and will be made available upon request to the public two years after the center fiscal year has ended.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
UAS-Based Radio Frequency Interference Localization Using Power Measurements
使用功率测量进行基于 UAS 的射频干扰定位
DOI:
10.33012/2024.19570
发表时间:
2024
期刊:
ION ITM 2024
影响因子:
--
作者:
[Smith, Casey, Yan, Haoming, Hafez, Osama Abdul, Hopwood, Jeremy, Joerger, Mathieu]
通讯作者:
Joerger, Mathieu
A Hybrid Model Reference Adaptive Control System for Multi-Rotor Unmanned Aerial Vehicles
多旋翼无人机混合模型参考自适应控制系统
DOI:
10.2514/6.2024-0755
发表时间:
2024
期刊:
SciTech
影响因子:
--
作者:
[Gramuglia, Mattia, Kumar, Giri Mugundan, L'Afflitto, Andrea]
通讯作者:
L'Afflitto, Andrea
DOI:
10.1002/acs.3631
发表时间:
2023-05
期刊:
International Journal of Adaptive Control and Signal Processing
影响因子:
3.1
作者:
[Andrea L’Afflitto]
通讯作者:
Andrea L’Afflitto
国内基金
海外基金
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