STTR Phase I: Virtual Interfaces using Multi-Protocol, Augmented-Reality Activation-Based Control Transfer
STTR Phase I: Virtual Interfaces using Multi-Protocol, Augmented-Reality Activation-Based Control Transfer
批准号:
2151524
负责人:
Dominick Lee
金额:
$25.6万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-09-01 至 2023-08-31
中文摘要
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英文摘要
The broader impact/commercial potential of this Small Business Technology Transfer (STTR) Phase I project provides virtual interfaces that can be dynamically customized to address the challenge of user adoption in augmented reality (AR) products. This project overcomes previous limitations for AR such as the lack of interoperability, user-acceptance, scalability, and application-aware user intent recognition. While the AR market is projected to grow, wearable collaboration has unexplored potential. Users empowered by this project may be able to easily collaborate alongside skilled experts as well as robotic interfaces in the same medium. Through contextually-aware dynamic controls, manufacturing businesses can lower the risk of human-error while increasing fulfillment capabilities, as employees working from home can stay physically connected and remain engaged with minimal compromise. The AR innovation proposed in this project has application across multiple industries, including manufacturing, training, and emergency simulations.This Small Business Technology Transfer (STTR) Phase I project aims to create a framework for scalable experimentation of virtual interfaces that empower users to search, tag, and store meaningful data using gesture interactions in a secure and private manner. This project seeks to provide context-based, hands-free interaction with wireless devices while minimizing the need to set up sensors (such as optical components or microphones) in controlled environments and providing visual feedback and accessibility to the end user. A wrist-worn wearable captures pre-trained gesture data, and a pair of augmented reality (AR) glasses identifies and analyzes an object within the context of said gestures to control a mechatronic device, such as a robot, to perform occupational tasks. This dynamic process uses factors such as the user’s gaze area, physical location, and computer application. The improvement upon gesture control may allow a separate visual unit, such as the AR glasses, to wirelessly receive and display the gesture intents and perform contextually-aware, meaningful interactions with a clear distinction across a plurality of devices or digitally tagged objects associated with a specific use-case.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.
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