嵌入式人在环网络物理系统快速开发框架

Shen Feng, F. Quivira, G. Schirner
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引用次数: 17

摘要

人在环网络物理系统(HiLCPS)提供辅助技术,增强人类与物理世界的互动,如自我进食、沟通和功能锁定的个人的移动性。HiLCPS应用程序通常实现为连接人类和物理环境的网络化嵌入式系统。由于与具有不同规格和物理位置(本地/远程)的硬件进行接口,开发HiLCPS应用程序具有挑战性。此外,虽然算法设计者在MATLAB中原型化应用程序受益于算法设计环境,但从原型化MATLAB应用程序到嵌入式解决方案之间的差距传统上需要大量的手工实现。为了快速开发嵌入式HiLCPS应用,本文提出了一个HiLCPS框架。该框架将类似的硬件类型分组为类,统一它们的访问,从而提供硬件和位置透明访问。该框架进一步集成了一个特定于领域的合成工具,称为Hsyn。Hsyn使算法设计人员能够在MATLAB中对可移植的、与硬件无关的应用程序进行原型设计,同时为嵌入式部署提供了自动路径,而无需嵌入式知识。我们用MATLAB中原型化的脑控轮椅应用程序演示了该框架的好处,该应用程序可以透明地访问具有本地或远程连接的各种EEG采集系统。然后,通过使用Hsyn,应用程序自动部署到配备定制设计的电生理采集斗篷的BeagleBone Black上。与手动嵌入式部署相比,Hsyn的生产率提高了6个数量级。轮椅基于人类意图推理进行逐步导航,平均每4秒在0.9置信阈值下,准确率为91%,超过9个用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Framework for Rapid Development of Embedded Human-in-the-Loop Cyber-Physical Systems
Human-in-the-Loop Cyber-Physical Systems (HiLCPS) offers assistive technology that augments human interaction with the physical world, such as self-feeding, communication and mobility for functionally locked-in individuals. HiLCPS applications are typically implemented as networked embedded systems interfacing both human and the physical environment. Developing HiLCPS applications is challenging due to interfacing with hardware with different specifications and physical location (local/remote). Also, while algorithm designers prototype applications in MATLAB benefiting from an algorithm design environment, the gap from prototyping MATLAB application to embedded solution traditionally requires significant manual implementation. In this paper, we propose a HiLCPS Framework for the rapid development of embedded HiLCPS applications. The framework groups similar hardware types to classes, unifying their access and with this offering both hardware and location transparent access. The framework furthermore incorporates a domain-specific synthesis tool, called Hsyn. Hsyn empowers algorithm designers to prototype a portable, hardware-agnostic application in MATLAB while offering an automatic path to embedded deployment without requiring embedded knowledge. We demonstrate the benefit of the framework with a brain-controlled wheelchair application prototyped in MATLAB that transparently accesses a variety of EEG acquisition systems with local or remote connections. Then, by using Hsyn, the application is automatically deployed to a BeagleBone Black equipped with a custom-designed electrophysiological acquisition cape. Hsyn shows six orders of magnitude of productivity gain compared to manual embedded deployment. The wheelchair performs stepwise navigated based on human intent inference with 91% accuracy at 0.9 confidence threshold every 4 seconds on average over 9 users.
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