Combat identification training using an augmented reality learning system

Loading...
Thumbnail Image
Issue Date
2013-02-14
Authors
Smith, Dustin C.
Chinn, Melissa E.
Advisor
Keebler, Joseph R.
Citation
Abstract

Combat identification (CID) is a high priority task throughout modern warfare. However, due to the quantity of fratricide accidents, it is reasonable to question the reliability of current CID training methods. With perceptual limitations (i.e. the keyhole effect), and 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? (d) Would training soldiers on both perspectives return superior combat identification performance? This research will examine training with an augmented reality learning system (BuildAR Software) to identify combat vehicles (i.e., Main Battle Tanks, and Personal Carriers). Therefore, subjects will be trained to identify tanks and personal carriers using either canonical or birds eye non-canonical perspectives. Further, training effectiveness will be measured using a computer-based assessment at the end of the study.

Table of Content
Description
Poster project completed at the Wichita State University Department of Psychology. Presented at the 10th Annual Capitol Graduate Research Summit, Topeka, KS, February 14, 2013.
publication.page.dc.relation.uri