Whole-body Exoskeletons for Advanced Vocational Enhancement


This project is funded through the Future of Work at the Human-Technology Frontier (FW-HTF) program at NSF. The project focuses on examining how powered exoskeletons can be integrated into the workspace to improve worker productivity, safety, and well-being. The project is composed of an interdisciplinary group of PI’s within VIrginia Tech whose diverse backgrounds enable gaining a full understanding of powered exoskeleton technology, from its technological advancements to its ergonomic impact on the wearer to its potential socioeconomic impact on industry at large. The project goals are to 1) understand the state of the art in powered exoskeleton technology in terms of controls and design. 2) Develop measures of the physical and mental impact that operating the exoskeleton has on the user, as well as the effectiveness of the human-robot interaction. 3) Advance the state of the art in exoskeleton controllers by leveraging whole-body-controllers used in humanoid robots, and by designing a human-in-the loop, adaptive controller that changes the assistance parameters within the exoskeleton to adjust to individual users. 4) Design and implement an augmented reality interface that improves the level of collaboration between the user and the exoskeleton, as well as the overall performance of the human-machine system. 5) Understand the potential personal impacts on workers, economic impact on companies, and broader socioeconomic impact that this technology would have if widely adopted throughout industry.
Powered, full-body exoskeletons have the potential to augment human physical capacity, thereby increasing productivity and lowering injury risks, while also preserving human skill for operating in dynamic, unstructured environments. Exoskeletons could also allow people with different physical abilities the opportunity to enter and stay employed in physically-demanding occupations. This project will complete critical fundamental research necessary to make exoskeletons effective for augmenting human performance in industrial use, such as manufacturing and warehousing. The project also examines the potential impacts this new technology may have on the sociotechnological landscape of jobs and workers. The team will develop a new control interface and an intelligent cognitive assistant to make exoskeleton use natural and intuitive, thus minimizing learning time and enabling adaptation to dynamic environments. The multimodal control interface will allow for augmentation of a user's perception and cognition when using physical capacity augmentation systems, and adaptive control of assistance from the exoskeleton according to user and context. The end results of this research will help workers to operate efficiently and seamlessly in dynamic and information-rich industrial settings. Industrial adoption of exoskeletons can have broad-reaching social and economic implications: by understanding the ramifications of this new technology for workforce diversification and labor market outcomes, the research will facilitate technology design choices that benefit the U.S. economy and U.S. workers. Collaboration with industry partners, including Sarcos Robotics and General Electric, will further insure industrial relevance of this project. This project will advance knowledge and state-of-the-art in exoskeleton control, human-robot cooperation, human factors, and augmented reality systems. An augmented reality interface to improve the user's mental model of exoskeleton capabilities and increase situational awareness will be developed, thereby enabling users to formulate new work strategies only afforded by the newly extended physical capabilities. In terms of human-robot cooperation, an adaptive predictor-based controller of high-level exoskeleton assistance parameters will be developed. This will account for the time varying response of the human to the system and the potential for different steady-state characteristics depending on the user, so as to achieve a tightly-coupled human-in-the-loop system. The assessments of learning and adaptation across a diverse range of workers will be key to making the developed designs more inclusive and effective, and to elucidating the effects of exoskeleton technologies on workforce diversification, including people with cognitive and physical impairments. While the impact of automation (replacing workers with technology) has been extensively studied in the economics literature, this work will generate the first empirical models of the effects of augmentation on worker productivity and well-being, industry profits, and the labor market in general.


Alexander Leonessa

Professor, Mechanical Engineering Department

Virginia Tech, Blacksburg, VA 24060

Divya Srinivasan

Professor, Industrial Engineering and Bioengineering

Clemson University, Clemson, SC 29634

Maury Nussbaum

Professor, Industrial and Systems Engineering Department

Virginia Tech, Blacksburg, VA 24060

Nathan Lau

Associate Professor, Industrial and Systems Engineering Department

Virginia Tech, Blacksburg, VA 24060

Suqin Ge
Associate Professor, Economics
Virginia Tech, Blacksburg, VA 24060