NRI: FND: End-User Robot Programming

NRI：FND：最终用户机器人编程

• 批准号: 2024561
• 负责人: Rodrigo Spinola
• 金额: $ 74.96万
• 依托单位: Virginia Commonwealth University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2024561&HistoricalAwards=false
• 关键词: NRI; FND; End; User; Robot

Collaborative robots, or robots that can safely work in close proximity to humans, promise to revolutionize society. Such robots could help the country remain competitive in the service and manufacturing industries. But this vision has not yet been achieved because programming robots remains difficult, time consuming, and, most importantly, only feasible by experts after years of training. This project seeks to remove this final barrier to progress by making collaborative robots programmable by their owners. That is, without any special training, to empower small business owners, lab technicians, and small-scale manufacturers to be able to program a robot to do meaningful tasks. Project outcomes will not only benefit American businesses by lowering costs and freeing human workers to complete higher-level tasks, they will also improve access to technology for many. Because the research will be conducted at a highly diverse university, in collaboration with a rural community college and a rural manufacturing research center, additional broad impacts will derive from exposing a diverse group of students to cutting edge technology they would otherwise never know existed. Furthermore, by conducting experiments and demonstrations at both rural sites the team will impart to the broader community a vision for future career choices while driving robot programming technology to the next level.Currently, the high cost of programming collaborative robots remains a major barrier to adoption. This project will create a suite of end-user programming languages that make common robot programming tasks accessible to novices, dramatically reducing this barrier to adoption. The work is based on two key insights. First, because collaborative robots offer unprecedented safety features, end-users can safely operate and program them. Second, by leveraging the last twenty years of progress in educational programming languages (e.g., MIT’s Scratch), interfaces can be created that support the programming of realistic tasks yet can be learned in minutes. The project will comprise four thrusts: (1) creation of a block-based robot programming environment that enables a large set of realistic tasks; (2) development of an in-line tutorial system for learning block-based programming without formal training; (3) implementation of a parallel programming language for multi-armed programming; and (4) definition of a multi-threaded programming approach for maximizing robot usage. This comprehensive set of tools will enable end-users to tackle many common robot programming tasks that are currently out of their reach. To ensure that the various approaches actually help end-users, they will be evaluated through extensive user studies run both on an urban and rural university campus. These studies, where subjects complete realistic tasks with the prototypes, will have three outcomes. First, preparing for the studies naturally hardens the research prototypes into high-quality software, allowing accurate evaluation. Second, the study will generate quantifiable results on the effectiveness of end-users programming with each tool. Third, through video analysis and interviews additional insight will be derived into further issues that hinder end-users, thereby laying the groundwork for the next round of innovations.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.

协作机器人，或可以安全地靠近人类工作的机器人，有望彻底改变社会。这样的机器人可以帮助该国在服务业和制造业保持竞争力。但这一愿景尚未实现，因为编程机器人仍然困难、耗时，而且最重要的是，只有经过多年培训的专家才能实现。这个项目试图通过使协作机器人的主人可编程来消除这个最后的障碍。也就是说，在没有任何特殊培训的情况下，让小企业主、实验室技术人员和小规模制造商能够给机器人编程，让它完成有意义的任务。项目成果不仅会降低成本，解放人力，让他们完成更高层次的任务，从而使美国企业受益，还会改善许多人获得技术的机会。由于这项研究将在一所高度多元化的大学进行，并与一所农村社区学院和一所农村制造业研究中心合作，因此，让不同群体的学生接触到他们原本不知道存在的尖端技术，将产生额外的广泛影响。此外，通过在这两个农村地区进行实验和演示，该团队将向更广泛的社区传授未来职业选择的愿景，同时将机器人编程技术推向一个新的水平。目前，协作机器人编程的高成本仍然是采用的主要障碍。该项目将创建一套终端用户编程语言，使新手可以访问常见的机器人编程任务，从而大大减少采用机器人的障碍。这项工作基于两个关键的见解。首先，由于协作机器人提供了前所未有的安全功能，终端用户可以安全地操作和编程它们。其次，利用过去二十年教育编程语言的进步（例如，麻省理工学院的Scratch），可以创建支持实际任务编程的接口，但可以在几分钟内学会。该项目将包括四个重点：(1)创建一个基于块的机器人编程环境，使大量现实任务成为可能；(2)开发在线导师制，无需经过正式培训即可学习基于块的编程；(3)多臂并行编程语言的实现；(4)定义了最大化机器人使用的多线程编程方法。这个全面的工具集将使最终用户能够解决许多目前超出他们能力范围的常见机器人编程任务。为了确保各种方法实际帮助最终用户，将通过在城市和农村大学校园进行广泛的用户研究来评估这些方法。在这些研究中，受试者用原型完成现实任务，将产生三种结果。首先，为研究做准备自然地将研究原型硬化为高质量的软件，从而允许进行准确的评估。其次，该研究将对使用每种工具的最终用户编程的有效性产生可量化的结果。第三，通过视频分析和访谈，将进一步深入了解阻碍最终用户的问题，从而为下一轮创新奠定基础。该奖项反映了美国国家科学基金会的法定使命，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。

项目成果

Language impact on productivity for industrial end users: A case study from Programmable Logic Controllers

• DOI: 10.1016/j.cola.2021.101087
• 发表时间: 2022-01
• 期刊: J. Comput. Lang.
• 作者: Felipe Fronchetti;Nico Ritschel;Reid Holmes;Linxi Li;Mauricio Soto;R. Jetley;Igor Scaliante Wiese;David C. Shepherd

Comparing Block-based Programming Models for Two-armed Robots

比较双臂机器人基于块的编程模型

• DOI: 10.1109/tse.2020.3027255
• 发表时间: 2020
• 期刊: IEEE Transactions on Software Engineering
• 影响因子: 7.4
• 作者: Ritschel, Nico;Kovalenko, Vladimir;Holmes, Reid;Garcia, Ron;Shepherd, David C.
• 通讯作者: Shepherd, David C.