Award Abstract # 2033615
B1 (Future Jobs and AI): Skill-XR: An Affordable and Scalable X-Reality (XR) Platform for Skills Training and Analytics in Manufacturing Workforce Education

NSF Org: ITE
Innovation and Technology Ecosystems
Recipient: PURDUE UNIVERSITY
Initial Amendment Date: August 20, 2020
Latest Amendment Date: June 22, 2021
Award Number: 2033615
Award Instrument: Cooperative Agreement
Program Manager: Linda Molnar
lmolnar@nsf.gov
 (703)292-8316
ITE
 Innovation and Technology Ecosystems
TIP
 Dir for Tech, Innovation, & Partnerships
Start Date: September 1, 2020
End Date: May 31, 2021 (Estimated)
Total Intended Award Amount: $5,000,000.00
Total Awarded Amount to Date: $1,470,935.00
Funds Obligated to Date: FY 2020 = $1,470,934.00
History of Investigator:
  • Karthik Ramani (Principal Investigator)
    ramani@purdue.edu
  • Kylie Peppler (Co-Principal Investigator)
  • Thomas Redick (Co-Principal Investigator)
  • Alexander Quinn (Co-Principal Investigator)
  • Niklas Elmqvist (Co-Principal Investigator)
Recipient Sponsored Research Office: Purdue University
2550 NORTHWESTERN AVE # 1100
WEST LAFAYETTE
IN  US  47906-1332
(765)494-1055
Sponsor Congressional District: 04
Primary Place of Performance: Purdue University
585 Purdue Mall
west lafayette
IN  US  47907-2088
Primary Place of Performance
Congressional District:
04
Unique Entity Identifier (UEI): YRXVL4JYCEF5
Parent UEI: YRXVL4JYCEF5
NSF Program(s): CA-FW-HTF: Convergence Acceler
Primary Program Source: 01001920DB NSF RESEARCH & RELATED ACTIVIT
01002021DB NSF RESEARCH & RELATED ACTIVIT
Program Reference Code(s):
Program Element Code(s): 096Y00
Award Agency Code: 4900
Fund Agency Code: 4900
Assistance Listing Number(s): 47.083

ABSTRACT

The broader impact and potential societal benefits of the SkillXR Convergence Accelerator Phase II project are training, pre- and upskilling, remote skilling, and enabling new insights in the manufacturing and education sectors. There is a multiplier effect on job growth in the national economy through expansions in manufacturing. As jobs and skills change and evolve, retraining and upskilling will become necessary steps towards economic sustainability, more importantly so as we recover during the COVID-19 pandemic. The aim of the SkillXR platform is to disrupt current modes of workforce development by eliminating the current need for expensive software development and consulting intermediaries to create and maintain augmented, virtual and mixed reality (XR) applications. Through our partnerships within the small and large manufacturing industry and workforce education, we will transition the future workforce from acquisition of apprenticeships to real-world profitable skills in emerging industries over the next decade. Our focused partnerships with small businesses, minority entrepreneurs, play museums, and rural education promotes equitable access. The general-purpose nature of SkillXR will amplify the impact beyond our initial planned manufacturing education area to become ubiquitous across many other fields including robotics, construction, plant operations, education, and eventually everyday spatial cognitive assistance. Our pre-upskilling and learning analytics platform is planned to impact tens of thousands in five to six years and millions within a decade. Rural communities especially will benefit, as manufacturing represents twice the amount of earnings there, versus non-rural areas.

The highly interdisciplinary team brings knowledge spanning manufacturing, computer vision and artificial intelligence (AI), spatial interfaces and interactions, learning sciences, learning analytics, cognitive psychology, and visual gamified interfaces. We will collaborate closely with key partners using a design-research driven convergence framework to develop and transform research-based prototypes into products and services to impact our skilled workforce and economy. The two sides of our emerging product platform will (1) enable the authoring of AI-based XR personalized training applications by subject matter experts (coaches, teachers, trainers), without the need for prior knowledge in programming or sophisticated applications, and (2) a low-cost AI-based hardware approach to get personalized user analytics of tasks ?on-the-job? for scalable workforce assessment and optimization. Our approach permits extreme flexibility for various industrial use cases, reusability through plug-and-play for millions of applications, as well as tracking end-user spatial and performance analytics across time. By combining both basic and applied research our team will develop several high-fidelity collaborative cloud-based architectures, and a series of reconfigurable and widely applicable workflows.

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.

PROJECT OUTCOMES REPORT

Disclaimer

This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.

There is a multiplier effect on job growth in the national economy through expansions in manufacturing. As jobs and skills change and evolve, retraining and upskilling has become a necessary step towards economic sustainability, as the COVID-19 pandemic continues. The aim of the SkillXR platform is to disrupt current modes of inefficient workforce development based on an age-old one-on-one training model. Although augmented and virtual reality offer possible solutions they need expensive software development and consulting intermediaries to create and maintain augmented, virtual and mixed reality (XR) applications. The societal benefits of the SkillXR Convergence Accelerator Phase II project are training, pre- and upskilling, remote skilling, and enabling new insights in the manufacturing and education sectors by developing accessible means of augmenting humans. Through our partnerships within the small and large manufacturing industry and workforce education, our convergence team developed and tested many proof of concept minimum viable prototypes. Our focused partnerships with small businesses, minority entrepreneurs, play museums, and rural education promoted equitable access. The general-purpose nature of SkillXR is now positioned to amplify the impact beyond our initial planned manufacturing education area to become ubiquitous across many other fields including robotics, construction, plant operations, education, and eventually everyday spatial cognitive assistance. Our pre-upskilling and learning analytics platform has been prototyped to demonstrate impact at scale. Rural communities especially will benefit, as manufacturing represents twice the amount of earnings there, versus non-rural areas.

The highly interdisciplinary team brings knowledge spanning manufacturing, computer vision and artificial intelligence (AI), spatial interfaces and interactions, learning sciences, learning analytics, cognitive psychology, and visual gamified interfaces. We collaborated closely with key partners using a design-research driven convergence framework to develop and transform research-based prototypes into products and services to impact our skilled workforce and economy. The two sides of our emerging product platform (1) enabled the authoring of AI-based XR personalized training applications by subject matter experts (coaches, teachers, trainers), without the need for prior knowledge in programming or sophisticated applications, and (2) a low-cost AI-based hardware approach to get personalized user analytics of tasks ?on-the-job? for scalable workforce assessment and optimization. Our approach permitted extreme flexibility for various industrial use cases, as well as tracking end-user spatial and performance analytics across time. By combining both basic and applied research our team developed several low to high-fidelity collaborative cloud-based architectures, and a series of reconfigurable and widely applicable workflows, and proved increase in productivity within our partners use cases as well as ability to author virtual and augmented reality in low-cost and scalable manner.


 

 


Last Modified: 09/29/2021
Modified by: Karthik Ramani

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