Combat identification using an augmented reality learning system
Date
2013-05-08Author
Smith, Dustin C.
Chinn, Melissa E.
Advisor
Keebler, Joseph R.Metadata
Show full item recordCitation
Dustin C. Smith, Melissa E. Chinn (2013). Combat Identification Using an Augmented Reality Learning System -- In Proceedings: 9th Annual Symposium: Graduate Research and Scholarly Projects. Wichita, KS: Wichita State University, p.79-80
Abstract
This research will examine training with an augmented reality learning system to identify combat vehicles. Due to the increase in use of unmanned vehicles (UVs) for missions, a question arises: How do we best train operators to perform well when presented with a combat identification task. More specifically: (a) Is training using canonical (front and side) views sufficient? (b) Due to
UAV perspective surveillance, are non-canonical/birds eye views necessary for optimal combat identification performance? (c) Would training with either perspective yield sufficient performance?
Description
Paper presented to the 9th Annual Symposium on Graduate Research and Scholarly Projects (GRASP) held at the Marcus Welcome Center, Wichita State University, May 8, 2013.
Research completed at the Department of Psychology, College of Liberal Arts & Sciences