Collaborative Research: CSR: Medium: Adaptive Environmental Awareness for Collaborative Augmented Reality
协作研究:企业社会责任:媒介:协作增强现实的自适应环境意识
基本信息
- 批准号:2312760
- 负责人:
- 金额:$ 40万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Continuing Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-10-01 至 2027-09-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Augmented reality (AR) represents an exciting new frontier for mobile applications, merging the physical and virtual worlds to facilitate real-time interactions between users and their surrounding physical environments. Next-generation AR is centered on interactive and environmentally-aware applications, which sense the state of the real world via computationally heavy perception algorithms, with results augmented in real-time for multiple users. However, current environmentally-aware AR applications are well-recognized to lack sufficient resilience for long-term, large-scale, and safety-critical deployments. The goal of this project is to exploit the collaborative nature of next-generation AR applications to provide reliable, real-time environmental awareness that can adapt to the surrounding environment, user mobility, and computing resource availability. The core insight of this project is that instead of simply competing with one another for network and compute resources, AR devices can collaborate with one another to run and adapt AR applications to optimize overall utility. The project will involve modeling environmental awareness and mobility patterns in AR, incorporating these models into an emulator to facilitate experimentation and training, and designing reinforcement learning policies that capture environmental awareness and dynamic user relationships. These policies will be deployed in a set of new collaborative AR applications, such as AR-based physical rehabilitation, and evaluated via expansive studies with multiple groups of users in a wide range of conditions. This project will lay the groundwork for resilient next-generation AR applications, which can benefit multiple domains, including retail, manufacturing, and healthcare. The project will develop an example next-generation AR-supported rehabilitation application, which will be showcased to clinicians across multiple hospital systems and will be integrated into the PIs’ K-12 and public outreach efforts. The multi-user AR emulator created as part of this project will be open-sourced to enable the development of a wide range of other applications and will be designed to be extensible to additional use cases, such as AR-aided human-robot collaboration. Moreover, the machine learning techniques for dynamic user collaboration developed as part of this project will be applicable to other cases in which multiple entities interact dynamically in a coordinated manner, such as supply chain management. The project will train several cohorts of undergraduate students, and results will be presented at multiple events and venues aimed at broadening participation in computing.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.
增强现实(AR)代表着移动应用的一个令人兴奋的新前沿,它融合了物理和虚拟世界,促进了用户与周围物理环境之间的实时交互。下一代AR以交互式和环保应用为中心,通过计算量大的感知算法感知现实世界的状态,并为多个用户实时增强结果。然而,目前具有环保意识的AR应用程序被公认为缺乏足够的弹性来进行长期、大规模和安全关键型部署。该项目的目标是利用下一代AR应用程序的协作特性来提供可靠、实时的环境感知,以适应周围环境、用户移动性和计算资源可用性。该项目的核心见解是,AR设备可以相互协作运行和调整AR应用程序,以优化整体效用,而不是简单地相互竞争网络和计算资源。该项目将涉及在AR中对环境意识和流动性模式进行建模,将这些模型整合到仿真器中以促进实验和培训,并设计可捕获环境意识和动态用户关系的强化学习策略。这些策略将部署在一组新的协作AR应用程序中,例如基于AR的物理康复,并通过在各种条件下对多组用户进行广泛研究来进行评估。该项目将为具有弹性的下一代AR应用程序奠定基础,这将使包括零售、制造业和医疗保健在内的多个领域受益。该项目将开发下一代AR支持的康复应用程序示例,该应用程序将向多个医院系统的临床医生展示,并将整合到私人投资机构的K-12和公共外联工作中。作为该项目的一部分创建的多用户AR仿真器将是开源的,以支持开发广泛的其他应用程序,并将被设计为可扩展到其他用例,例如AR辅助的人与机器人协作。此外,作为本项目的一部分开发的用于动态用户协作的机器学习技术将适用于多个实体以协调方式动态互动的其他情况,例如供应链管理。该项目将培训几批本科生,结果将在多个活动和场所展示,旨在扩大对计算的参与。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。
项目成果
期刊论文数量(0)
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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Maria Gorlatova其他文献
Did You Do Well? Real-Time Personalized Feedback on Catheter Placement in Augmented Reality-Assisted Neurosurgical Training
你做得好吗?
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Sangjun Eom;Tiffany S Ma;Neha Vutakuri;Alexander Du;Zhehan Qu;Joshua Jackson;Maria Gorlatova - 通讯作者:
Maria Gorlatova
BiGuide: A Bi-level Data Acquisition Guidance for Object Detection on Mobile Devices
BiGuide:移动设备上物体检测的双层数据采集指南
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Lin Duan;Ying Chen;Zhehan Qu;Megan McGrath;E. Ehmke;Maria Gorlatova - 通讯作者:
Maria Gorlatova
AR Simulations in VR: The Case for Environmental Awareness
VR 中的 AR 模拟:环境意识案例
- DOI:
10.1109/vrw62533.2024.00289 - 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Ryleigh Byrne;Zhehan Qu;Christian Fronk;Sangjun Eom;T. Scargill;Maria Gorlatova - 通讯作者:
Maria Gorlatova
Maria Gorlatova的其他文献
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{{ truncateString('Maria Gorlatova', 18)}}的其他基金
HCC: Small: Robust Object Detection for Mobile Augmented Reality in the Wild
HCC:小型:用于野外移动增强现实的稳健物体检测
- 批准号:
2231975 - 财政年份:2023
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
CAREER: Foundations of IoT-Supported Mobile Augmented Reality
职业:物联网支持的移动增强现实的基础
- 批准号:
2046072 - 财政年份:2021
- 资助金额:
$ 40万 - 项目类别:
Continuing Grant
CNS Core: Small: Collaborative Research: Towards Intelligent Multi-User Augmented Reality with Edge Computing
CNS 核心:小型:协作研究:利用边缘计算实现智能多用户增强现实
- 批准号:
1908051 - 财政年份:2019
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
CSR: Small: Collaborative Research: Multi-tier Service Architecture in IoT-Edge-Cloud-Paradigms
CSR:小型:协作研究:物联网-边缘-云-范式中的多层服务架构
- 批准号:
1812797 - 财政年份:2018
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
CSR: Small: Collaborative Research: Multi-tier Service Architecture in IoT-Edge-Cloud-Paradigms
CSR:小型:协作研究:物联网-边缘-云-范式中的多层服务架构
- 批准号:
1903136 - 财政年份:2018
- 资助金额:
$ 40万 - 项目类别:
Standard Grant
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