FW-HTF-RM: Collaborative Research: Future of Construction Work at the Human-Technology Frontier

FW-HTF-RM：协作研究：人类技术前沿建筑工作的未来

• 批准号: 1928527
• 负责人: Marissa Shuffler Porter
• 金额: $ 40万
• 依托单位: Clemson University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1928527&HistoricalAwards=false
• 关键词: FW; HTF; RM; Collaborative; Research

The construction industry faces many workforce-related challenges, including a shortage of skilled workers and high accident and injury rates. The use of robotic technologies to augment construction workers can enable new construction techniques and work opportunities. This project seeks to transform the nature of construction work by removing barriers to the formation of human-robot teams on the jobsite. Working together with skilled trade workers, robots have the potential to lower construction costs through more precise cutting and placing actions that reduce waste. Human-robot teams can also increase safety and efficiency by reducing the risk of overexertion and injury to workers. The investigators will address three specific barriers to the widespread adoption of robotics on the construction site: (1) the lack of clearly defined and fully structured robotic tasks for trade work; (2) the need to understand how robots will be integrated into predominantly human-centric trade worker teams; and (3) the need to identify new knowledge and resource requirements that will support robots on the construction jobsite. This project explores convergent solutions to overcoming barriers to human-robot teaming in construction, using methods from computer science, construction engineering, and social science to: (a) re-define construction tasks by translating the means and methods of trade work into common actions that can be interpreted and performed by robotic systems, and (b) explore how robotic systems can be integrated into current and future human-robot construction teams, as an integral part of the worker, knowledge, task, and resource networks on the jobsite. To achieve these aims, this research will surface which construction tasks can and cannot be automated or augmented using robotics. Of the processes that are well-suited to robotics, basic design information will be converted into defined tasks and ultimately into instructions for the robot and the conditions needed to perform the action. Shared mental models for introducing robots within trade worker teams will be created, which will assist in determining the role of human-made robotic systems, as either active team participants or simply passive tools. Lastly, a meta-network analysis will study the potential vulnerability of human-robot teams to identify the risks and opportunities for improving the reliability of construction project delivery. These efforts will result in a risk framework for understanding the direct (e.g., safety) and indirect (e.g., network vulnerabilities) risks, as well as unintended consequences, emerging from the integration of robots in the construction work context. Collectively, this research will advance the potential for human-robot teams in the construction industry.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.

建筑业面临着许多与劳动力相关的挑战，包括熟练工人短缺以及事故和受伤率高。使用机器人技术来增加建筑工人可以实现新的建筑技术和工作机会。该项目旨在通过消除工地上形成人机团队的障碍来改变建筑工作的性质。与熟练的贸易工人一起工作，机器人有可能通过更精确的切割和放置动作来减少浪费，从而降低建筑成本。人机团队还可以通过降低工人过度劳累和受伤的风险来提高安全性和效率。调查人员将解决在建筑工地上广泛采用机器人技术的三个具体障碍：（1）缺乏明确定义和结构完整的机器人贸易工作任务;（2）需要了解机器人如何融入以人为本的贸易工人团队;（3）需要确定新的知识和资源需求，以支持建筑工地上的机器人。该项目探讨了克服建筑中人机合作障碍的融合解决方案，使用计算机科学，建筑工程和社会科学的方法：（a）重新界定建筑工作，将行业工作的手段和方法转化为可由机器人系统解释和执行的共同行动，以及（B）探索机器人系统如何能够集成到当前和未来的人类-机器人施工团队中，作为工地上的工人、知识、任务和资源网络的组成部分。为了实现这些目标，这项研究将揭示哪些施工任务可以和不能使用机器人自动化或增强。在非常适合机器人的过程中，基本设计信息将被转换为定义的任务，并最终转换为机器人的指令和执行动作所需的条件。将创建用于在贸易工人团队中引入机器人的共享心智模型，这将有助于确定人造机器人系统的作用，无论是主动团队参与者还是被动工具。最后，元网络分析将研究人类-机器人团队的潜在脆弱性，以确定提高建筑项目交付可靠性的风险和机会。这些努力将产生一个风险框架，用于理解直接（例如，安全性）和间接（例如，网络漏洞）风险，以及意外的后果，从机器人在建筑工作环境中的整合出现。总的来说，这项研究将推动建筑行业中人机团队的潜力。该奖项反映了NSF的法定使命，并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，被认为值得支持。

项目成果

The forgotten teammate: Considering the labor perspective in human-autonomy teams

• DOI: 10.1016/j.chb.2023.107763
• 发表时间: 2023-03
• 期刊: Comput. Hum. Behav.
• 作者: Sydney R. Begerowski;Katelyn N. Hedrick;Flanagan Waldherr;L. Mears;Marissa L. Shuffler

Examining the Effects of Cognitive Assistive Agents on Team Coordination in Manufacturing Teams

• DOI: 10.1177/1071181322661401
• 发表时间: 2022-09
• 期刊: Proceedings of the Human Factors and Ergonomics Society Annual Meeting
• 作者: Begerowski S.R.;Waldherr F.;Biddlecom J.;Traylor A.;Krugh M.;Mears L.;Shuffler M.L.