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Proceedings Paper

IITET and shadow TT: an innovative approach to training at the point of need
Author(s): Andrew Gross; Favio Lopez; James Dirkse; Darran Anderson; Stephen Berglie; Christopher May; Susan Harkrider
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Paper Abstract

The Image Intensification and Thermal Equipment Training (IITET) project is a joint effort between Night Vision and Electronics Sensors Directorate (NVESD) Modeling and Simulation Division (MSD) and the Army Research Institute (ARI) Fort Benning Research Unit. The IITET effort develops a reusable and extensible training architecture that supports the Army Learning Model and trains Manned-Unmanned Teaming (MUM-T) concepts to Shadow Unmanned Aerial Systems (UAS) payload operators. The training challenge of MUM-T during aviation operations is that UAS payload operators traditionally learn few of the scout-reconnaissance skills and coordination appropriate to MUM-T at the schoolhouse. The IITET effort leveraged the simulation experience and capabilities at NVESD and ARI’s research to develop a novel payload operator training approach consistent with the Army Learning Model. Based on the training and system requirements, the team researched and identified candidate capabilities in several distinct technology areas. The training capability will support a variety of training missions as well as a full campaign. Data from these missions will be captured in a fully integrated AAR capability, which will provide objective feedback to the user in near-real-time. IITET will be delivered via a combination of browser and video streaming technologies, eliminating the requirement for a client download and reducing user computer system requirements. The result is a novel UAS Payload Operator training capability, nested within an architecture capable of supporting a wide variety of training needs for air and ground tactical platforms and sensors, and potentially several other areas requiring vignette-based serious games training.

Paper Details

Date Published: 9 June 2014
PDF: 10 pages
Proc. SPIE 9076, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XI, 90760D (9 June 2014); doi: 10.1117/12.2053760
Show Author Affiliations
Andrew Gross, Trideum Corp. (United States)
Favio Lopez, Trideum Corp. (United States)
James Dirkse, Trideum Corp. (United States)
Darran Anderson, Trideum Corp. (United States)
Stephen Berglie, KINEX (United States)
Christopher May, U.S. Army Night Vision & Electronic Sensors Directorate (United States)
Susan Harkrider, U.S. Army Night Vision & Electronic Sensors Directorate (United States)

Published in SPIE Proceedings Vol. 9076:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications XI
Daniel J. Henry; Davis A. Lange; Dale Linne von Berg; S. Danny Rajan; Thomas J. Walls; Darrell L. Young, Editor(s)

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