FW-HTF-P: Enabling Multifaceted Collaboration between Humans, Robots, and Remote Workers for Future Distributed Manufacturing

“人类技术前沿（FW-HTF-P）未来工作”项目的总体目标是推动跨分布式地点的人机团队协作，以提高未来制造业劳动力的安全性、灵活性和生产力。这一结果将缓解美国日益扩大的制造业技能差距，这一差距是由劳动力老龄化、工作与生活缺乏平衡以及工作需求与技能项目之间的地理不匹配造成的。具体来说，该项目开发奖将支持创建一个概念框架和现实的实验测试平台，与来自工业利益相关者的指导一起，使现场人类和机器人工人与远程人类工人合作的混合团队能够进行研究，并严格评估对运营和组织绩效的相关影响。这些新的人机协作模式允许专业工人与现场员工进行远程协作，从而促进了服务不足的社区工人的融入，这些社区工人接受的培训较少或身体或精神能力较差。他们将提供实践监督学习的机会，让新员工提高他们的技能，增加他们的专业价值。在体力紧张的工作任务中使用机器人队友将减少肌肉骨骼损伤，从而提高生活质量，延长制造业工人的生产生涯。此外，该奖项将为工程和社会/行为科学专业的学生提供跨学科的实践研究经验，并为STEM领域中代表性不足的群体提供教育机会。本项目发展奖的目标是：1)对制造环境中采用人-机器人（远程人类）或HR(H)协作的推动者和障碍有一个基本的了解，以支持未来工作的设计，这些工作将从HR(H)协作过程中获益最多；2)创建一个概念框架和物理测试平台，以支持探索和评估不同工作设计和界面的人力资源(H)协作；3)评估具有代表性的制造协作场景（例如，车辆和飞机的维护和修理），以了解影响人力资源(H)协作的信任、绩效和安全的因素。这项工作的主要贡献有三个方面。首先，将获得来自行业合作伙伴（制造业利益相关者和机器人制造商）的直接知识和观点，以检查在未来分布式制造中使用HR(H)协作的可行性和效益。其次，人力资源(H)测试平台的开发将支持在未来的工作设计中评估人力资源(H)协作，包括各种工作接口和工作任务，以获得人力资源(H)协作技术的基础知识。该试验台将培养在机器人、人的因素、生物力学和心理学方面获得多人与多机器人协作的多学科知识的机会。第三，在人力资源(H)协作中，影响工人绩效、生产力、安全和健康的关键因素将通过人类和机器人之间不同程度协作的初始代表性制造协作场景进行调查。这些项目开发活动将大大提高在未来分布式制造环境中实现人力资源(H)协作的知识和技术水平。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。

The overarching goal of this Future of Work at the Human Technology Frontier (FW-HTF-P) project is to advance the state-of-the art of human-robot teams collaborating across distributed locations, in order to promote improved safety, flexibility, and productivity for the future manufacturing workforce. The result will mitigate the growing manufacturing skills gap in the US, caused by an aging workforce, lack of work-life balance, and geographical mismatches between job demands and skills programs. Specifically, this Project Development award will support the creation of a conceptual framework and realistic experimental testbed that will, together with guidance gathered from industrial stakeholders, enable studies of mixed teams of on-site human and robot workers collaborating with remote human workers, with rigorous assessment of the associated impacts on operations and organizational performance. These new modes of human-robot collaboration allow expert workers to remotely collaborate with on-site employees, facilitating the inclusion of underserved communities of workers with less training or reduced physical or mental capacity. They will provide hands-on supervised learning opportunities to allow newer workers to enhance their skills and increase their professional value. The use of robot teammates for physically stressful work tasks will reduce musculoskeletal injury, and thus improve quality of life and extend productive careers for manufacturing workers. Additionally this award will support hands-on cross-disciplinary research experiences for engineering and social/behavioral science students, and provide educational opportunities for groups under-represented in the STEM fields.The goals of this Project Development award are to 1) generate a fundamental understanding of the promoters of and barriers to the adoption of Human-Robot-(remote Human), or HR(H), collaboration in manufacturing environments, to support the design of future work that will most benefit from HR(H) collaboration processes; 2) create a conceptual framework and a physical testbed that will support exploration and assessment of HR(H) collaboration with different work designs and interfaces; and 3) evaluate representative manufacturing collaboration scenarios (e.g., vehicle and aircraft maintenance and repair) to understand factors affecting trust, performance, and safety of HR(H) collaboration. Primary contributions of this work are threefold. First, direct knowledge and perspectives from industry partners (manufacturing industry stakeholders and robot manufacturers) will be obtained to examine the feasibility and benefits of using HR(H) collaboration in future distributed manufacturing. Second, the development of an HR(H) testbed will support assessing HR(H) collaboration in future work designs, including various work interfaces and work tasks, to gain fundamental knowledge of HR(H) collaborative technologies. The testbed will foster opportunities to gain multidisciplinary knowledge of multi-human and multi-robot collaboration in terms of robotics, human factors, biomechanics, and psychology. Third, key factors affecting worker performance, productivity, and safety and health within the HR(H) collaboration will be investigated, via initial representative manufacturing collaboration scenarios with varying degrees of collaboration between humans and robots. These project development activities will substantially advance the knowledge and state-of-the-art in realizing HR(H) collaboration in future distributed manufacturing environments.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.