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

• 批准号: 2312762
• 负责人: Jiasi Chen
• 金额: $ 40万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2312762&HistoricalAwards=false
• 关键词: Collaborative; Research; CSR; Medium; Adaptive

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) 代表了移动应用程序的一个令人兴奋的新领域，它融合了物理世界和虚拟世界，以促进用户与其周围物理环境之间的实时交互。下一代 AR 以交互式和环境感知应用程序为中心，这些应用程序具有感知能力。通过计算量大的感知算法来了解现实世界的状态，并为多个用户实时增强结果。然而，众所周知，当前的环境感知 AR 应用缺乏足够的长期、大规模和安全的弹性。 -批判的该项目的目标是利用下一代 AR 应用程序的协作特性，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。 AR 设备不是简单地相互竞争网络和计算资源，而是可以相互协作来运行和调整 AR 应用程序，以优化整体效用。该项目将涉及对 AR 中的环境意识和移动模式进行建模，并将这些模型纳入其中。一个模拟器来促进实验和训练，并设计强化学习策略来捕获这些政策将部署在一系列新的协作 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个用户组进行广泛的研究进行评估。该项目将开发一个下一代 AR 支持的康复应用程序示例，并将向多个医院系统的殖民者展示。将被纳入 PI 的 K-12 和公共作为该项目一部分创建的多用户 AR 模拟器将开源，以支持开发各种其他应用程序，并将设计为可扩展至其他用例，例如 AR 辅助人类机器人。此外，作为该项目的一部分开发的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交互的其他情况，例如供应链管理。该项目将培训几批本科生。 ，结果将在多个活动中公布该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。