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

人类技术前沿未来工作（FW-HTF-P）项目的总体目标是推进人类-机器人团队在分布式位置协作的最新技术，以促进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，这是由劳动力老龄化、缺乏工作与生活平衡以及工作需求与技能计划之间的地理不匹配造成的。具体而言，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，以及从工业利益相关者那里收集的指导，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的研究成为可能，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家工作人员与现场员工远程协作，促进了培训较少或身体或精神能力下降的工人社区的参与。他们将提供实践监督学习的机会，让新工人提高他们的技能，提高他们的专业价值。使用机器人队友进行体力紧张的工作任务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，该奖项将支持工程和社会/行为科学学生的实践跨学科研究经验，并为STEM领域代表性不足的群体提供教育机会。该项目开发奖的目标是：1）对采用人-机器人技术的推动者和障碍有基本的了解，（远程人力）或HR（H），制造环境中的协作，以支持未来工作的设计，这将最大限度地受益于HR（H）协作流程; 2）创建一个概念框架和一个物理测试平台，以支持探索和评估人力资源（H）与不同工作设计和界面的协作;以及3）评估代表性的制造协作场景（例如，车辆和飞机维护和维修），以了解影响HR（H）协作的信任、绩效和安全性的因素。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，以研究在未来分布式制造中使用HR（H）协作的可行性和好处。第二，HR（H）测试平台的开发将支持在未来的工作设计中评估HR（H）协作，包括各种工作界面和工作任务，以获得HR（H）协作技术的基础知识。该试验台将促进获得多人和多机器人协作的多学科知识的机会，包括机器人技术，人为因素，生物力学和心理学。第三，将通过人类和机器人之间具有不同程度协作的初始代表性制造协作场景，调查HR（H）协作中影响工人绩效、生产力以及安全和健康的关键因素。这些项目开发活动将大大推进知识和国家的最先进的实现人力资源（H）在未来的分布式制造环境的协作。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.