NRI: FND: Multi-Manipulator Extensible Robotic Platforms

长期以来，机器人学一直强调“危险、肮脏或乏味”的任务。该项目旨在提高熟练专家的工作效率，而不是自动化低技能的大规模制造任务。该项目将实现由领域专家与机器人协作执行的定制、专业和利基任务的自动化。实验室科学家依靠对样本的精确处理来收集数据。该项目将开发合作机器人自动化工具，使科学探索成为可能。这些工具将包括可为不同应用定制的开源运动平台、可在不接触对象的情况下移动对象的新型末端执行器，以及可用于创作使用这些工具进行的工作流程的软件编程环境。这些工具允许科学家将精确的操作委托给机器人，而不会损失探索和迭代开发实验和工作流程的能力。这项研究将通过提供与许多科学领域相关的低成本和可访问的基础设施来拓宽和多样化获得自动化技术的途径。该研究将建立最终用户可以为特定应用任务定制的协作式工作流工具。它将为超声波操纵提供新型末端效应器，包括操纵被捕获的粉末和液体等应用。它将为自动在多个末端执行器之间切换的运动平台提供新的设计模式。这些运动平台将是可定制的，应用专家能够在现场生产它们，而不需要额外的机器人专业知识。它将提供软件工具，用于控制这些从最终用户角度开发的终端执行器和运动平台，提供抽象概念，允许领域专家定义和执行协作机器人工作流程。这项工作将通过开发非接触式操纵、可定制的协作机器人和自动化工作流程的迭代设计，极大地推动机器人学和人机交互方面的研究工作。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。

For a long time, robotics has emphasized "dangerous, dirty, or dull" tasks. This project aims to make skilled experts more productive rather than automate lower skilled mass-manufacturing tasks. The project will enable automation of custom, specialized, and niche tasks conducted collaboratively by domain experts together with robots. Laboratory scientists rely on precise and accurate manipulation of samples for the gathering of data. This project will develop co-botic automation tools that enable scientific exploration. These tools will include open-source motion platforms which can be customized for different applications, novel end effectors which can move objects without touching them, and software programming environments that can be used for authoring workflows that will be conducted with these tools. These tools allow scientists to delegate the precise manipulation to a robot without loss of the ability to explore and iteratively develop experiments and workflows. This research will broaden and diversify access to automation technology by providing low-cost and accessible infrastructure that is relevant to many scientific domains.The research will establish tools for co-botic workflows which end-users can customize for application specific tasks. It will contribute novel end-effectors for ultrasonic manipulation, including for applications such as manipulating trapped powders and liquids. It will contribute new design patterns for motion platforms which automatically change between multiple end-effectors. These motion platforms will be customizable, with application experts able to produce them in the field without additional expertise in robotics. It will contribute software tools for controlling these end-effectors and motion platforms developed from an end-user perspective, providing abstractions that allow domain experts to define and execute collaborative robotic workflows. This work will substantially advance research efforts in robotics and human-machine interaction by developing contactless manipulation, customizable co-bots, and iterative design of automated workflows.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.