Smart instrumented training ranges: bringing automated system solutions to support critical domain needs. (July 2013)

• Record Type: Journal Article
• Authors: Sadagic, Amela; Kölsch, Mathias; Welch, Greg; Basu, Chumki; Darken, Chris; Wachs, Juan P.; Fuchs, Henry; Towles, Herman; Rowe, Neil; Frahm, Jan-Michael; Guan, Li; Kumar, Rakesh; Cheng, Hui
• Is Part Of: Journal of defense modeling and simulation. Volume 10:Number 3(2013)
• Page Start: 327
• Page End: 342
• Publication Date: 2013-07
• Subjects: Instrumented training ranges -- multi-sensor systems -- automated behavior analysis -- behavior synthesis -- computer vision -- after-action-review -- simulations; Military art and science -- Computer simulation -- Periodicals; 355.0011305
• DOI: 10.1177/1548512912472942
• Languages: English
• ISSNs: 1548-5129

Abstract

The training objective for urban warfare includes acquisition and perfection of a set of diverse skills in support of kinetic and non-kinetic operations. The US Marines (USMC) employ long-duration acted scenarios with verbal training feedback provided sporadically throughout the training session and at the end in a form of an after-action review (AAR). The inherent characteristic of training ranges for urban warfare is that they are the environments with a high level of physical occlusion, which causes many performances not to be seen by a group of instructors who oversee the training. We describe BASE-IT (Behavioral Analysis and Synthesis for Intelligent Training), a system in development that aims to automate capture of training data and their analysis, performance evaluation, and AAR report generation. The goal of this effort is to greatly increase the amount of observed behavior and improve the quality of the AAR. The system observes training with stationary cameras and personal tracking devices. It then analyzes movement and body postures, measures individual and squad-level performance, and compares it to standards and levels of performance expected in given situations. An interactive visualization component delivers live views augmented with real-time analytics and alerts; it also generates a personalized AAR review in a three-dimensional virtual or mixed reality environment, indexed by automatically extracted salient events and accompanied by summary statistics of unit performance. The approaches presented in the system have the potential to radically change the analysis and performance assessment on physical training ranges and ultimately this type of training itself.