IUCRC: Phase 2: Center for Unmanned Aircraft Systems

IUCCRC：第二阶段：无人机系统中心

• 批准号: 1650468
• 负责人: Eric Frew
• 金额: $ 50万
• 依托单位: University of Colorado at Boulder
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-04-01 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1650468&HistoricalAwards=false
• 关键词: IUCRC; Phase; Center; Unmanned; Aircraft

The Center for Unmanned Aircraft Systems (C-UAS) addresses the issues common to the unmanned aircraft system (UAS) industry that limit widespread application across national security, scientific, civil, and commercial domains. Research within the UAS industry is driven by both technical gaps existing for specific high-value applications and the current under-developed regulatory framework that is needed for integration of UAS into the national airspace. The full value of unmanned aircraft systems, especially for a broad range of scientific and civil applications, cannot be realized without significant multidisciplinary research efforts such as those proposed here. Toward that goal, C-UAS investigates and develops new algorithms, architectures, and operational procedures for unmanned aircraft systems. The center contributes to the advancement of the state of the art for UAS through its research at the center's universities and by training graduate students in areas supporting the advancement of UAS. The research pursued in C-UAS has potential application to unmanned aircraft of all sizes. The primary focus of research activities, however, is on small unmanned aircraft systems (SUAS), which feature aircraft with wingspans in the 1 ft to 8 ft range. C-UAS university sites have distinguished themselves with their experimental flight test demonstrations on these smaller platforms. The research interests and needs of industry in the area of UAS align well with the skills, knowledge, and background of the university participants in the center. Research focus areas for the University of Colorado Boulder site can be described in terms of (1) technical areas and (2) application areas. Technical topic areas in which the University of Colorado has particular strength and interest include: (i) Airborne communication networks and network-enabled autonomy (e.g., methods for routing data through mobile ad-hoc networks and for accessing dispersed computing), (ii) environmental sensing (e.g., novel sensor development and planning algorithms for targeted observation of environmental phenomena), (iii) human-autonomy interaction (e.g., natural language interfaces and humans-as-sensor models for communication of spatial information), (iv) assured autonomy and user trust (e.g., measures of machine self-confidence and assessment of their impact on user trust), (v) UAS traffic management (e.g., investigating the impact of weather on small UAS operations), and (vi) guidance and control with in complex winds (e.g., implementing control algorithms for wind gust disturbance rejection or for energy harvesting). Application topic areas in which the University of Colorado has particular strength and interest include: (i) Atmospheric science with emphasis on severe weather, (ii) Cooperative distributed sensor fusion and target tracking, and (iii) Search and rescue. Specific research projects proposed by University of Colorado faculty members in these technical and application areas are selected annually by the Industry Advisory Board (IAB).

无人机系统中心（C-UAS）致力于解决无人机系统（UAS）行业的常见问题，这些问题限制了国家安全，科学，民用和商业领域的广泛应用。UAS行业内的研究是由特定高价值应用的现有技术差距和将UAS集成到国家空域所需的当前欠发达的监管框架驱动的。无人驾驶航空器系统的全部价值，特别是在广泛的科学和民用应用方面的价值，如果没有本文所建议的重大多学科研究努力，就无法实现。为了实现这一目标，C-UAS研究并开发了用于无人机系统的新算法、架构和操作程序。该中心通过在该中心的大学进行研究，并通过在支持UAS发展的领域培训研究生，为UAS最先进的发展做出贡献。在C-UAS中进行的研究对各种规模的无人驾驶飞机都有潜在的应用。然而，研究活动的主要重点是小型无人驾驶飞机系统（SUAS），其特点是翼展在1英尺至8英尺范围内的飞机。C-UAS大学站点因在这些较小平台上进行实验飞行测试演示而脱颖而出。工业界在无人机系统领域的研究兴趣和需求与该中心大学参与者的技能，知识和背景非常一致。科罗拉多大学博尔德分校的研究重点领域可以分为（1）技术领域和（2）应用领域。科罗拉多大学具有特别优势和兴趣的技术主题领域包括：（i）机载通信网络和网络使能的自治（例如，用于通过移动的自组织网络路由数据和用于访问分散计算的方法），（i i）环境感测（例如，新的传感器开发和规划算法，用于有针对性地观察环境现象），（iii）人类自主交互（例如，自然语言接口和用于空间信息通信的人作为传感器模型），（iv）保证的自主性和用户信任（例如，机器自信度的测量和它们对用户信任的影响的评估），（v）UAS业务管理（例如，调查天气对小型UAS操作的影响），以及（vi）在复杂风中的引导和控制（例如，实现用于阵风干扰抑制或用于能量收集的控制算法）。科罗拉多大学具有特别优势和兴趣的应用主题领域包括：（一）大气科学，重点是恶劣天气，（二）合作分布式传感器融合和目标跟踪，以及（三）搜索和救援。由科罗拉多大学教师在这些技术和应用领域提出的具体研究项目每年由行业咨询委员会（IAB）选择。

项目成果

Forward Adaptive Transfer of Gaussian Process Regression

• DOI: 10.2514/1.i010437
• 发表时间: 2017-04
• 期刊: J. Aerosp. Inf. Syst.
• 作者: Neeti Wagle;E. Frew

Collaborative human-autonomy semantic sensing through structured POMDP planning

通过结构化 POMDP 规划实现协作式人类自主语义感知

• DOI: 10.1016/j.robot.2021.103753
• 发表时间: 2021
• 期刊: Robotics and Autonomous Systems
• 影响因子: 4.3
• 作者: Burks, Luke;Ahmed, Nisar;Loefgren, Ian;Barbier, Luke;Muesing, Jeremy;McGinley, Jamison;Vunnam, Sousheel
• 通讯作者: Vunnam, Sousheel

Collaborative Semantic Data Fusion with Dynamically Observable Decision Processes

协作语义数据融合与动态可观察决策过程

• 发表时间: 2020
• 期刊: 2019 22th International Conference on Information Fusion (FUSION
• 作者: Burks, L.;Ahmed, N.
• 通讯作者: Ahmed, N.

Optimal Continuous State POMDP Planning With Semantic Observations: A Variational Approach

• DOI: 10.1109/tro.2019.2933720
• 发表时间: 2018-07
• 期刊: IEEE Transactions on Robotics
• 影响因子: 7.8
• 作者: Luke Burks;Ian Loefgren;N. Ahmed

Adaptive Simulation-Based Training of Artificial-Intelligence Decision Makers Using Bayesian Optimization

使用贝叶斯优化对人工智能决策者进行基于自适应仿真的训练

• DOI: 10.2514/1.i010553
• 发表时间: 2018
• 期刊: Journal of Aerospace Information Systems
• 影响因子: 1.5
• 作者: Israelsen, Brett;Ahmed, Nisar;Center, Kenneth;Green, Roderick;Bennett, Winston
• 通讯作者: Bennett, Winston