CAREER: Toolkits for Digital/Physical Workflows

职业：数字/物理工作流程工具包

• 批准号: 2339273
• 负责人: Nadya Peek
• 金额: $ 71.31万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-06-15 至 2029-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2339273&HistoricalAwards=false
• 关键词: CAREER; Toolkits; Digital; Physical; Workflows

This project contributes toolkits to support designers creating systems that include both hardware and software by lowering the threshold to using automation in their workflows. While automation can increase precision and efficiency, setting up new automated workflows can be costly, requiring expertise and significant up-front engineering time. Because of this cost, automation is largely used for tasks that are sufficiently frequently used that this up-front investment can be recouped, such as in the context of mass production. Domain experts working at smaller scales or with niche workflows cannot benefit in the same ways, hindering their progress. In contrast, this research prioritizes a broader community of fabrication practitioners whose varied requirements demand a broad diversity of automation strategies. This project will help practitioners identify viable opportunities for automation in their work, contribute open-source software and hardware toolkits with which practitioners can author their own automated digital/physical workflows, and organize communities using and maintaining these technologies. These outputs will provide assistance to a wide range of people developing innovative human-centered systems that use digital/physical workflows in their chosen application areas through a series of courses and workshops that will be taught using these technologies and through their open-source release.This research includes three main areas: formative research on the work of practitioners who span digital and physical spaces, such as fabricators or laboratory scientists; the development of novel devices and hardware modules for automating physical processes including motion control and active end effectors; and end-user software that scaffolds the authoring of automated digital/physical workflows, including modules that support the creation of task-specific artificial intelligence (AI) models for automated event detection. This human-centered approach—where users can refine their models and workflows as they collect additional data—leverages practitioners’ understanding of their own data during collection. By collaborating with experts across different domains through formative studies and design workshops, toolkits and systems from this research will generalize to multiple application areas. Other people will have opportunities to engage with this technology and learn about automation through courses and workshops in community spaces like Do-It-Yourself (DIY) biolabs and makerspaces. Furthermore, this research will contribute design recommendations for open-source hardware that is replicable and can be tailored by end-users. Together, these contributions comprise both valuable toolkits for automating digital/physical workflows and implications for future systems design.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.

该项目提供工具包，以支持设计人员通过降低在工作流程中使用自动化的门槛来创建包括硬件和软件的系统。虽然自动化可以提高精度和效率，但设置新的自动化工作流程可能成本高昂，需要专业知识和大量的前期工程时间。由于这一成本，自动化主要用于那些使用频率足够高的任务，从而可以收回前期投资，例如在大规模生产的情况下。在较小规模或利基工作流程中工作的领域专家无法以同样的方式受益，从而阻碍了他们的进步。相比之下，本研究优先考虑更广泛的制造从业者社区，他们的不同要求需要广泛多样的自动化策略。该项目将帮助从业人员确定工作自动化的可行机会，提供开源软件和硬件工具包，从业人员可以使用这些工具包编写自己的自动化数字/物理工作流程，并组织使用和维护这些技术的社区。这些成果将通过一系列课程和研讨会，帮助人们开发创新的以人为本的系统，在他们选择的应用领域使用数字/物理工作流程，这些课程和研讨会将使用这些技术并通过其开源版本进行教学。这项研究包括三个主要领域：对跨越数字和物理空间的从业者的工作进行形成性研究，例如制造商或实验室科学家;开发新的设备和硬件模块，用于自动化物理过程，包括运动控制和主动末端执行器;以及最终用户软件，其支撑自动化数字/物理工作流程的创作，包括支持创建用于自动事件检测的特定任务人工智能（AI）模型的模块。这种以人为本的方法-用户可以在收集其他数据时改进他们的模型和工作流-利用了从业者在收集期间对自己数据的理解。通过与不同领域的专家合作，通过形成性研究和设计研讨会，本研究的工具包和系统将推广到多个应用领域。其他人将有机会参与这项技术，并通过DIY生物实验室和创客空间等社区空间的课程和研讨会了解自动化。此外，这项研究将有助于开源硬件的设计建议，是可复制的，可以由最终用户量身定制。这些贡献共同构成了用于自动化数字/物理工作流程的宝贵工具包以及对未来系统设计的影响。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。