Collaborative Research: NRI: Understanding Underlying Risks and Sociotechnical Challenges of Powered Wearable Exoskeleton to Construction Workers

各种可穿戴机器人正在兴起，以解决建筑行业中人类操作的挑战。这些解决方案的目的是通过提供升降支撑、分散重量和姿势矫正来减少工人的工伤。尽管这些可穿戴机器人在减少建筑工人的体力需求方面具有潜力，但目前的知识体系并没有充分了解将这些机器人应用于建筑工地的风险和挑战。鉴于建筑行业中大量的背部相关伤害，本研究有助于支持动力背部支撑机器人在建筑行业的设计和广泛使用。通过了解这些可穿戴机器人在建筑工地的潜在生理、心理和社会技术风险，该项目旨在克服在建筑行业大规模采用这些可穿戴机器人的挑战，从而提高美国建筑行业750万工人的安全和生产力。此外，本研究将为制造商提供经验证据，为更广泛的体型和尺寸设计更具适应性，可访问性，可接受性和舒适的可穿戴机器人，以考虑到建筑行业的不同人群。这项跨学科研究旨在整合各种关键创新的进展，包括沉浸式技术、生理传感、可穿戴机器人和组织心理学，以确定建筑行业外骨骼的潜在物理、心理和社会技术风险。这个项目的技术目标分为三个重点。第一个重点将利用社会技术角度来确定建筑行业采用外骨骼的障碍和促进因素。第二个推力将生成一个沉浸式交互式虚拟现实测试平台，用于对使用这些外骨骼执行的不同施工任务进行可行的模拟。特别是，这一重点将开发一个以用户为中心的模拟工作空间，以无缝地检查不同的相互作用，以便对相关的身体和心理风险进行安全可行的评估。第三个重点将设计一个新的以工人为中心的风险评估框架，以评估建筑工人使用这些外骨骼的生理和心理风险。具体来说，这一重点将整合人工智能和客观评估，在生理和心理生理数据之间建立新的解释管道，包括局部肌肉疲劳、跌倒风险、关节过伸、认知工作量、信任和工人在施工任务中的警惕性。这三个研究目标将辅以一个综合评估计划，其中包括三个中间评估，以确保项目的可靠性。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。

A wide range of wearable robots are emerging as solutions to human operation challenges in the construction sector. The aim for such solutions is to reduce work-related physical injuries among workers by providing lift support, weight dispersion, and posture correction. In spite of the potential of these wearable robots in reducing the physical demands of construction workers, the current body of knowledge does not provide an adequate understanding of the risks and challenges of incorporating these robots on construction sites. Given the large number of back-related injuries in the construction industry, this research contributes to supporting the design and widespread use of powered back-support robots in the construction industry. By understanding the potential physical, psychological, and socio-technical risks of these wearable robots at construction sites, this project aims to overcome the challenges of scalable adoption of these wearable robots in the construction industry, thereby improving the safety and productivity of 7.5 million workers in the U.S. construction sector. Furthermore, this research will provide empirical evidence for manufacturers to design more adaptable, accessible, acceptable, and comfortable wearable robots for a wider range of body shapes and sizes to take into account diverse populations of the construction sector.This interdisciplinary research seeks to integrate advances across a diverse spectrum of critical innovations, including immersive technologies, physiological sensing, wearable robots, and organizational psychology, to identify the underlying physical, psychological, and socio-technical risks of exoskeletons in the construction sector. The technical aims of this project are divided into three thrusts. The first thrust will utilize a socio-technical perspective to identify barriers and facilitators to the adoption of exoskeletons in the construction industry. The second thrust will generate an immersive and interactive virtual-reality testbed for the feasible simulation of different construction tasks executed using these exoskeletons. In particular, this thrust will develop a user-centered, simulated workspace to seamlessly examine different interactions for a safe and feasible evaluation of pertinent physical and psychological risks. The third thrust will design a novel worker-centered risk assessment framework for evaluating the physical and psychological risks of using these exoskeletons for construction workers. Specifically, this thrust will integrate artificial intelligence and objective evaluations to develop a new interpretive pipeline between physiological and psychophysiological data with local muscular fatigue, fall risk, joint hyperextension, cognitive workload, trust, and vigilance of workers during the construction tasks. These three research aims will be complemented by a comprehensive evaluation plan featuring three intermediate evaluations to ensure the reliability of the 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.