1. Army Research Lab Advanced Training & Simulation Division
Julio de la Cruz
Chief Engineer for Synthetic Environment
19 September 2016

2. State-of-the-Art Collaborative Environment
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State-of-the-Art Collaborative Environment
SFC Paul Ray Smith, Simulation and Training Technology Center
Adaptive Tutoring Lab
Virtual/Augmented Reality Lab
Gaming Lab
Visualization Testbed
Medical Research/Tissue Lab
Open Campus Laboratories at UCF Institute for Simulation and Training
Army UARC - Institute for Creative Technologies at USC
BACKGROUND: On October 1, 2002, Technology Development Center became provisionally part of RDECOM and was redesignated the STTC. The remaining elements of STRICOM became the Program Executive Office of Simulation, Training, and Instrumentation. In November 2003, STTC was renamed in honor of SFC Paul Ray Smith, who later was posthumously awarded the Medal of Honor for actions in Operation Iraqi Freedom.
FACILITIES:
The center supports a wide portfolio of modelling, simulation and training research from adaptive training and tutoring to synthetic tissue research
COLLABORATION WITH THE UNIVERSITY OF CENTRAL FLORIDA’S INSTITUTE FOR SIMULATION AND TRAINING:
Second largest university in the Nation and first to offer a PhD program in modelling and simulation – STTC has several engineers that are in the processes of receiving their PhD’s or have already graduated.
Collaborative robotics and human factors laboratories
STTC workforce is augmented both in engineering and administratively through the UCF contract
ARL-HRED STTC manages the ICT one of three Army URACs (University Affiliated Research Centers.
Based in Los Angeles the ICT facilitates collaboration with major movie and game makers to generate some of the best graphics to create realistic computer-generated characters in to enhance virtual characters.
Prototypes provide engaging experiences to improve skills in decision-making, cultural awareness, leadership and coping.
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Mission and Vision
Mission - Conduct Simulation & Training Research and Development to enhance Warfighter Mission Effectiveness.
Vision - To be the Center of Innovation for Simulation & Training Research and Technology Development for the Warfighter.
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4. ATSD Simulation and Training Technology Portfolio
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ATSD Simulation and Training Technology Portfolio
Future Training Environment Core Campaign Enablers (CCEs)
Intelligent Tutors and Artificial Intelligence
Single Synthetic Environment
One World Terrain
Big Data and Point of Need
Adaptive Tutors
Virtual Humans
Virtual Reality
Mixed/Augmented Reality
Dynamic/Interactive Effects
Physics Based Models
Simulation Tools / Architecture
Soldier Centric Learning
Other Core Campaign Enablers (CCEs) and Key Campaign Initiative (KCI)
Live Training
Medical Simulation
Cyber Training
Training Effectiveness
Hybrid Laser, Sensors
Predictive Technologies
Human Simulators
Medical Simulations
Cyber training simulations
Attack/Defense
Training Effectiveness STO
Automated Tools
COBWebS
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5. Research Park UNIVERSITY of CENTRAL FLORIDA ARMY NAVY ARMY ARMY
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Research Park
AT&T
L3 COM
National Center for Simulation
LOCKHEED MARTIN
Booz-Allen & Hamilton
SAIC
SFC Smith Center
Institute for Simulation & Training
RAYTHEON
GENERAL DYNAMICS
NORTHRUP
GRUMMAN
CSC
UNIVERSITY High School
Georgia Tech
Research Institute
UNIVERSITY of CENTRAL FLORIDA
ARMY
COAST GUARD
ARMY
AIR FORCE
MARINE CORPS
NAVY
PEO STRI ARMY
Partnership 3
Partnership 1
Partnership 2
Tech Point II
DeFlorez
Annex
Research Commons
Tech Point I
ARMY
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6. Synthetic Natural Environments (SNE)
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Synthetic Natural Environments (SNE)
DISTANCE HALL
Purpose:
Research, tools and methods to improve the speed and fidelity of environment (data) information delivered to the trainee in support of Training Aid Devices (TAD).
Products:
High fidelity and dynamic SNE products (i.e. terrain) available where and when needed to conduct training, simulation and mission planning operations
Data exploitation capabilities
Terrain Generation / Runtime
Terrain Storage and Generation
SNE Tools and Algorithms
SNE Integration Testbed
Payoff:
Advanced tools and methodologies to support future model development for run-time generation of dynamic environments.
Innovative methods to support high-fidelity synthetic environment representation of the real battlefield
Improved standards, interfaces and protocols to support rapid, common data transfer.
Program Schedule
Elements 18 19 20 21 22
Data Exploitation
Terrain Generation / Runtime
Terrain Storage and Distribution
SNE Services and Algorithms 2 4 2 5 3 5 3 6
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7. Map of the world? Ref: www.sedris.org
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Map of the world?
Map of the world must have containers representing all datum types to support All environmental domains..air, land and sea.
Ref:
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Feasible?
Must preserve real world properties critical to producer and consumer per use case
Data Must be realistic and be
A best-approximation of specific or typical place and time
Physically consistent:
Rivers: flow downhill
Roads: consistently model and attributed
Terrain, atmosphere, ocean and space: content agree
Structures: constantly model and attributed for underground and above ground data
Support all environmental domains
In compliance with data representation model(s)
Correlation with other “runtime” application dataset formats produced from the same datasets
Efficient interchange model must exist
Sharing and re-use
Tools and applications
Open Standards, Software and API must exist.
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9. Achievable? ---Though Problem Community buy in and requirements ?
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Achievable?
---Though Problem
Community buy in and requirements ?
Set requirements from DoD
The Services has spent >>$1B on generating terrain databases for various games, sims and training systems
On average, it still takes 13 months to manually create the average terrain dataset for M&S (1km x 1km)- specific to the army
The fidelity & correctness of the databases are nowhere close to rendering /simulation capabilities available today
Set requirements/interest from Business
Commercial processes and proprietary products
Profit, market share and quick return in investment are the drivers
Extensibility and customization from a business perspective
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Challenges?
M&S and Training Perspective: All these views must coexist .
Persistent and consistent to support multiple and different views
Ref:
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11. Thank You. US Army, Flickr.com Ref: www.sedris.org
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Thank You.
U.S. Soldiers assigned to 1st Battalion, 10th Special Forces Group (Airborne) practice a variety of shooting techniques with their M4A1 rifles at Panzer Range Complex in Boebligen, Germany, Jan. 23, 2015.(U.S. Army photo by Visual Information Specialist Adam Sanders/Released)
US Army, Flickr.com
Ref:
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12. BACKUP SLIDES - APPROVED FOR PUBLIC RELEASE

13. M&S Database Generation Tools
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M&S Database Generation Tools
SEAGUL (Scene Extraction and Autonomous Generation of Urban Landscapes)-Processes LIDAR data to extract building footprints and terrain surface
U2MG (Urban and Underground Model Generator)-Generates building models and interiors according to footprint and structure parameter inputs
RUGUD (Rapid Unified Generation of Urban Databases)- RUGUD Toolkit generates terrain mesh and integrates point/areal features from source data
SHADE (SHared Architecture For Dynamic Environments (SHADE)- Reusable, extensible dynamic environment capability
DTAS (Dynamic Terrain Applied Solutions) Research to extend physics-based models/ interactions and weather effects with dynamic terrain, including subsurface effects
RPEL ( Real-time Physics Effects Library Time Physics) It is a physics effects, or damage engine
GETIG (Game Environment Terrain Interactive Generator) a set of automated tools for converting, manipulating, optimizing, and enhancing military source data for game-based virtual environments
RAVEN (Reusable Architecture for Visualizing Environments) – Visual framework that allows rapid prototype capability
LTF (Layered Terrain Format)- RDECOM evolvement of the Live Terrain Format into a Live Virtual Capability for embedded applications
ASCEND - Research technology to support on-demand, cloud-based automation of GIS processing workflows, including database production, from source to Soldier
AGUS (Automated Generation of Underground Structures) Automatic generation of underground structures for use in both visual and non-visual formats
Geospatial Correlation- C-nergy is toolsets provide the ability to conduct automated and interactive analysis of data integrity
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14. Complex Implementation
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Complex Implementation
Example of a legacy system database generation process
Ref:
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