SBIR-STTR Award

Modeling Human Interfaces and Behaviors in Dismounted Soldier Training Environments
Award last edited on: 11/5/2009

Sponsored Program
SBIR
Awarding Agency
DOD : Army
Total Award Amount
$1,468,619
Award Phase
2
Solicitation Topic Code
A07-157
Principal Investigator
James A Saffold

Company Information

Research Network Inc (AKA: RNI)

3400 Blue Springs Road Suite 110
Kennesaw, GA 30152
   (678) 354-0152
   support@resrchnet.com
   www.resrchnet.com
Location: Single
Congr. District: 11
County: Cobb

Phase I

Contract Number: ----------
Start Date: ----    Completed: ----
Phase I year
2008
Phase I Amount
$69,998
This research will specifically look at the dismounted soldier simulation environment and aim to make significant advances for the command and control of computer generated forces such as Blue Force and unmanned platforms. These advances will use intelligent human interfaces, particularly voice recognition and other multi-modalities such as hand signaling.

Keywords:
Gaming, Human Interface Device (Hid), Modality, Simulation Bridge, Commercial Integration

Phase II

Contract Number: ----------
Start Date: ----    Completed: ----
Phase II year
2009
Phase II Amount
$1,398,621
RNI with team member Technical Solutions, Inc. (TSI/TERI) is proposing a unique integrated solution to this problem. An innovative effort to design, develop and demonstrate Multi-Modal Interfaces for Synthetic Training Environments for effective training. The system will allow live humans as team or squad leaders to utilize a suite of interface devices to control and interact with automated forces and the simulation environment. It is well known that small teams of dismounts often use non-verbal communications to direct subordinates. These “gestures” may also be repeated to by sub-commanders to other team members. Similarly, non-verbal responses may be used providing full 2-way communication of key tactical methods and status within the team. Current semi-automated force (SAF) applications do not include non-verbal communication capabilities and often have limited or poor world response and interaction capabilities. World interaction includes any number of items such as the ability to “use” a light switch or recognize potential danger indicated by an opened door or broken window. The proposed concept addresses the limitations of current systems artificial intelligence (AI) and input devices available for humans-in-the-loop. The concept also allows full functionality in software without requiring use of specialized equipment.

Keywords:
Games, Training, Multi-Modal, Interfaces, Man-Worn, Motion, Capture, Aar