FW-HTF-P: Human-Robot Collaboration for Enhancing Work Capabilities

人类-技术前沿未来工作(FW-HTF)项目的研究目标是创建一种配对工具，以识别制造工作场所中机器人能力可以增强或增强人类工人以提高生产率和安全性的机会。这个规划项目将通过对美国经济中1000多种职业中每一种工作所需的关键任务的现有数据库中的任务进行建模，来调查将人类工人整合到工作流程中的可能性。项目团队还将与业界接触，以了解任务建模的结果与实际工作之间的差异。成功的项目成果将包括围绕未来协作技术的知识进步，以及围绕美国工人和智能机器人工作场所助理之间的关系和共存的基础知识的进步。一系列密集的研讨会将促进流程优化、劳动经济学和公共卫生专家之间的新研究合作，为FW-HTF长期研究计划建立一个多学科研究团队。这个规划项目将把最先进的工作设计和任务分配方法和工具应用于那些显示出协作机器人集成的高潜力的工作和职业，以更好地了解人-机器人合作中的技术挑战。研究小组将对美国劳工部职业信息网(O*Net)数据库中的候选任务子集进行建模，并应用基于优化的工具来探索人类-机器人合作的可能性，并调查人类-机器人合作对站和系统级性能的影响。项目组将分析模型化工作配置对生产率、人体工程学和兼容性等关键因素的影响。项目完成后，团队将更好地了解工作模型和真实工作之间的差异，以及将协作机器人集成到现有制造环境中的测量挑战和限制。研讨会活动将促进与流程优化、劳动经济学和公共卫生方面的专家进行新的研究合作，以建立一个长期计划的多学科研究团队。该项目的最终目标是发展必要的研究人员、研究基础设施和基础工作，以扩大在FW-HTF完整研究项目层面上研究未来技术、未来工人和未来工作的机会。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。

The research objective of this Future of Work at the Human-Technology Frontier (FW-HTF) project is to create a matchmaking tool to identify opportunities in manufacturing workplaces where robot capabilities can augment or enhance human workers to improve productivity and safety. This planning project will investigate the possibility to integrate human workers into work processes by modeling tasks from an existing database of critical tasks required to perform each of more than 1000 occupations within the US economy. The project team will also engage with industry to understand differences between the results of task modeling and real work. Successful project outcomes will include the advancement of knowledge around future collaborative technologies, as well as the advancement of fundamental knowledge around the relationship and co-existence between American workers and intelligent robotic workplace assistants. A series of intensive workshops will foster new research collaborations between experts in process optimization, labor economics, and public health to build a multidisciplinary research team for a long-term FW-HTF research initiative. This planning project will apply state-of-the-art work-design and task-allocation methods and tools to jobs and occupations that show high potential for the integration of collaborative robots to gain a better understanding of the technical challenges in human-robot teaming. The research team will model a subset of candidate tasks from the US Department of Labor Occupational Information Network (O*NET) database and apply optimization-based tools to explore possibilities for human-robot teaming and to investigate the impact of human-robot teaming on both station and system level performance. The project team will analyze the effects of modeled work configurations on key factors such as productivity, ergonomics, and compatibility. Upon project completion, the team will better understand the discrepancy between work models and real-world work, as well as the measurement challenges and constraints in the integration of collaborative robots to existing manufacturing environments. Workshop activities will foster new research collaborations with experts in process optimization, labor economics, and public health to build a multidisciplinary research team for a long-term initiative. The ultimate goal of this project is to develop the necessary research personnel, research infrastructure, and foundational work to expand the opportunities for studying future technology, future workers, and future work at the level of a FW-HTF full research project.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.