skilleARn: Software for the Design and Development of AR task/instruction Delivery

Back to all technologies
Download as PDF
2019-RAMA-68475
Researchers at Purdue University have developed a framework for skill transfer and task learning in augmented reality (AR) applications. Current AR systems aimed at task training struggle with the adaptability of skill difficulty and proper training of workers for unexpected troubleshooting. This technology solves these problems through machine learning data-driven techniques that quantify dependent and independent variables and determine which skills are most relevant to transfer from a task. Furthermore, this technology includes a prediction model to track a novice's performance over time and emphasize skills that are necessary to succeed in the task at hand. This technology also can be used in design theory in the implementation of AR instructions and task delivery to decrease the time required for novices to learn unfamiliar tasks.

Advantages:
-Increase efficiency
-Adjust "cognitive load" based on users skill level

Potential Applications:
-AR assisted efficient task completion
-Maintenance, repair, and overhaul of manufacturing systems
Nov 27, 2019
Utility Patent
United States
(None)
(None)

Oct 30, 2019
Provisional-Patent
United States
(None)
(None)

Nov 28, 2018
Provisional-Patent
United States
(None)
(None)
Purdue Office of Technology Commercialization
The Convergence Center
101 Foundry Drive, Suite 2500
West Lafayette, IN 47906

Phone: (765) 588-3475
Fax: (765) 463-3486
Email: otcip@prf.org