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

建筑行业面临着许多与劳动力相关的挑战，包括熟练工人的短缺和高事故和伤害率。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在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降低建筑成本，从而减少浪费。人-机器人团队还可以通过减少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广泛采用机器人技术的三个具体障碍：(1)缺乏明确定义和完全结构化的贸易机器人任务；(2)需要了解机器人将如何融入以人类为中心的贸易工人团队；(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。本项目利用计算机科学、建筑工程和社会科学的方法，探索克服建筑中人机合作障碍的融合解决方案，以：(a)通过将贸易工作的手段和方法转化为可以由机器人系统解释和执行的共同行动，重新定义施工任务；(b)探索如何将机器人系统集成到当前和未来的人-机器人施工团队中，作为工地上工人、知识、任务和资源网络的组成部分。为了实现这些目标，本研究将揭示哪些建筑任务可以或不能使用机器人实现自动化或增强。在非常适合机器人技术的过程中，基本的设计信息将转化为定义的任务，并最终转化为机器人的指令和执行动作所需的条件。将创建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角色，无论是作为积极的团队参与者还是仅仅作为被动的工具。最后，元网络分析将研究人机团队的潜在脆弱性，以识别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，用于理解机器人在建筑工作环境中的集成所产生的直接（例如，安全）和间接（例如，网络漏洞）风险，以及意想不到的后果。总的来说，这项研究将推进建筑行业人机团队的潜力。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 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.