Collaborative Research: FW-HTF-R: Wearable Safety Sensing and Assistive Robot-Worker Collaboration for an Augmented Workforce in Construction

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Construction workers exert intense physical effort and experience serious safety and health risks in hazardous working environments. Thus, the construction industry is one of the highest-risk sectors in the US. A significant shortage of skilled workers in the construction industry amplifies the need to improve workers’ safety and health. Furthermore, the current workforce is aging and retiring; approximately 39% of construction workers were between 45-64 years old in 2020. Low interest among young adults and very low representation of women workers (only 4% in 2020) is exacerbating the existing labor shortage. As a result, there is an urgent need to develop new technology that keeps workers safe and injury-free, makes the industry more inclusive and economically sustainable, and eventually changes negative images that construction jobs are unsafe, low tech, and too male-dominated. The objective of this FW-HTF research project is to develop wearable safety sensing and assistive robot-worker collaboration for an augmented workforce, thereby improving worker retention and attracting women and young workers to construction careers. The researchers will also develop a number of integrated research and education programs to attract students from underrepresented groups into engineering and involve undergraduate students in research.Although robotics technologies are increasingly used, most research focuses on how they support construction tasks and yield economic benefits. Few studies discuss how to deploy wearable exoskeletons to prevent work-related musculoskeletal disorders and improve workers’ safety and health. New interventions are needed to address current safety and health knowledge gaps, identify social and economic benefits, risks, and barriers to the adoption of emerging technologies, and contribute to the development of an inclusive, diverse, and sustainable workforce in construction. Wearable devices, machine learning, and virtual-, augmented- and mixed-reality technologies offer great promise for revolutionizing existing practices in construction. This potential motivates the PIs to develop an integrated, multidisciplinary approach to bring these emerging technologies to individual workers, organizations, and the construction industry to enhance worker safety and health, improve productivity, address gender- and age-related labor shortages and expand employment opportunities. In this research project, the team of researchers plans to develop wearable occupational safety sensing and assistive robotic collaboration technology for skilled construction workers. Specifically, this project will emphasize: (1) machine learning-enabled, real-time worker activity recognition and pose estimation; (2) user-centered design of soft exoskeletons; (3) mixed reality-enhanced work skill transferring and workplace-based learning; (3) wearable safety sensing and assistive robotic collaboration for an augmented workforce; (4) analyses of social-economic impacts of the proposed technology; and (5) pilot studies, industrial deployment and workforce training. Academic collaborations and multi-stakeholder partnerships will provide the intellectual and personnel infrastructure necessary to address the multi-disciplinary, multi-faceted challenges by integrating best practices in construction with emerging technologies.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.