NSF Org:	SES Division of Social and Economic Sciences
Recipient:	WASHINGTON STATE UNIVERSITY
Initial Amendment Date:	August 25, 2021
Latest Amendment Date:	August 25, 2021
Award Number:	2128398
Award Instrument:	Standard Grant
Program Manager:	Songqi Liu soliu@nsf.gov  (703)292-8950 SES  Division of Social and Economic Sciences SBE  Directorate for Social, Behavioral and Economic Sciences
Start Date:	January 1, 2022
End Date:	December 31, 2025 (Estimated)
Total Intended Award Amount:	$210,000.00
Total Awarded Amount to Date:	$210,000.00
Funds Obligated to Date:	FY 2021 = $210,000.00
History of Investigator:	Olusola Adesope (Principal Investigator) olusola.adesope@wsu.edu
Recipient Sponsored Research Office:	Washington State University 240 FRENCH ADMINISTRATION BLDG PULLMAN WA  US  99164-0001 (509)335-9661
Sponsor Congressional District:	05
Primary Place of Performance:	Washington State University PO Box 641060 Pullman WA  US  99164-1060
Primary Place of Performance Congressional District:	05
Unique Entity Identifier (UEI):	XRJSGX384TD6
Parent UEI:
NSF Program(s):	FW-HTF Futr Wrk Hum-Tech Frntr
Primary Program Source:	01002122DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):	063Z
Program Element Code(s):	103Y00
Award Agency Code:	4900
Fund Agency Code:	4900
Assistance Listing Number(s):	47.075

ABSTRACT

Construction is a $10 trillion industry that employs about 180 million workers worldwide. However, the future of construction work is at crossroads. First, productivity in construction work has been stagnant relative to other industries (e.g., manufacturing), and the industry has historically been slow to adopt innovations that affect efficiency. Second, it has been difficult to offset the aging and retiring workforce with younger and more diverse workers, causing the workforce supply to fall short of rising demand. This is mainly because construction work tends to be physically strenuous leading to occupational hazards that often force workers to retire early. Robotization has been suggested as a potential solution to these problems. However, the unstructured nature of construction work presents several technical, social and economic impediments that hinder the direct adoption and integration of such innovations by the construction industry. For construction workers, robotic technology can only be transformative if it allows them to channel their passion for the work while avoiding the chronic pain and health outcomes associated with its physical demands.

This project investigates if construction work can be conceived as a human-robot partnership, where human workers play the critical role of planning the work, and training and supervising robotic assistants to adapt to presented workspace conditions and perform useful work. The project team is integrating advances in interactive task learning, mixed reality, and reinforcement learning to enable construction workers to naturally collaborate with robot assistants through direct physical interaction and virtual supervision and training. For such a symbiotic human-robot partnership to benefit construction workers and result in widespread deployment, workers need to be equipped with new skills. The project team is exploring new educational and professional development programs to support worker aspirations for upskilling and lifelong learning, and to open avenues for people of diverse abilities to be productive members of the construction workforce. Tight-knit partnerships with industry collaborators will inform the project activities and provide access to construction work sites and training facilities for testing and evaluation.

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.

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