Objective Live-Training Infantry Performance Metrics for Automated After Action Review
Navy SBIR FY2008.2

Sol No.: Navy SBIR FY2008.2
Topic No.: N08-111
Topic Title: Objective Live-Training Infantry Performance Metrics for Automated After Action Review
Proposal No.: N082-111-0258
Firm: Primordial, Inc.
1835 Energy Park Drive
Saint Paul, Minnesota 55108
Contact: Randy Milbert
Phone: (651) 659-6762
Web Site: http://primordial.com
Abstract: To conduct effective after-action reviews (AARs) for United States Marine Corps (USMC) live training exercises, instructors need to automate the analysis of captured data and minimize their level of effort. In partnership with ScenPro and Cubic Defense Applications, Primordial proposes Overlord, software that automatically tags relevant events buried in mountains of raw data captured during training, allowing USMC instructors to efficiently evaluate trainees against their expert counterparts. Overlord is based on the ViSSA (Virtual Soldier Skills Assessment) software which ScenPro developed under a phase II Small Business Research and Development (SBIR) contract in 2005. ViSSA automatically detects significant events in a Distributed Interactive Simulation (DIS)/High-Level Architecture (HLA)-based virtual environment. Overlord will interface with live instrumented training ranges such as Cubic's Advanced Systems Architecture for Urban Live Training (ASAULT). Cubic is a world leader in instrumented live training. Composed entirely of commercial off-the-shelf (COTS) hardware, ASAULT provides a state of the art position tracking system that reports trainee positions seamlessly between indoor and outdoor environments. ASAULT ranges use industry-standard data formats such as DIS, HLA, and the Test and Training Enabling Architecture (TENA). Overlord will be capable of analyzing object data captured in all of these formats.
Benefits: Primordial, ScenPro, and Cubic envision the following benefits and applications: 1) Automatically tagging events where Marine trainee performance deviates from that of experts frees instructors from tedious analysis. 2) Comparing expert and trainee team performance facilitates higher-level analysis even when input data is individual-based. 3) Comparisons are made in an objective fashion based on well-accepted rules and instructor judgments, freeing AARs from subjectivity. 4) Preparing AAR materials immediately following the exercise makes instructor feedback more relevant to trainees. 5) ASAULT allows Overlord to scale from single room-clearing exercises to full-blown military operations in urban terrain cities. 6) ViSSA allows Overlord to avoid duplicating work by leveraging advances made in virtual training, such as checking whether trainees are breaking rules that encode expert behavior. 7) Overlord is applicable to both military and law enforcement agencies (e.g., Special Weapons and Tactics), who often require similar training and after action review capabilities.