Automated Modeling and Simulation Tool for Lightening the Load of Warfighters

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-08-M-0272
Agency Tracking Number: N08A-019-0299
Amount: $69,970.00
Phase: Phase I
Program: STTR
Awards Year: 2008
Solitcitation Year: 2008
Solitcitation Topic Code: N08-T019
Solitcitation Number: 2008.A
Small Business Information
SANTOS, INC.
Oakdale Research Campus, Iowa City, IA, 52242
Duns: 149037256
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Karim Abdel-Malek
 Director, CCAD
 (319) 335-5676
 amalek@engineering.uiowa.edu
Business Contact
 Rich Lineback
Title: VP, Engineering
Phone: (319) 335-5723
Email: rlinebac@engineering.uiowa.edu
Research Institution
 THE UNIV. OF IOWA
 Twila F Reighley
 2 Gilmore Hall
Iowa City, IA, 52242
 (319) 335-2123
 Nonprofit college or university
Abstract
Today’s Warfighter often carries an inordinate load that can lead to injuries and encumbered performance. Equipment is distributed among squad members with little, if any regard for differences in strength and anthropometry. Consequently, the current focus on human-centric design requires a modeling and simulation tool that can reduce the load Warfighters carry and can help distribute equipment among squad member more efficiently. This, in turn, increases effectiveness, saves money, saves time, and saves lives. Santos, Inc. and The University of Iowa’s Virtual Soldier Research (VSR) Program have experience and expertise tailored to providing precisely this kind of tool. The proposed research will leverage VSR’s long standing partnerships with the U.S. military and industries, and will center around SantosTM, which is a complete, high fidelity, autonomous digital human who predicts posture, motion, strength, muscle fatigue, physiological indices, and more. Phase I of this work will provide a feasibility study for four components of a comprehensive toolkit: 1) squad optimization for automatically distributing equipment among squad members based on mission and Warfighter characteristics, 2) physics-based dynamic motion prediction for predicting how Warfighters move, and 3) equipment models that link with motion prediction to determine how Warfighters interact with equipment.

* information listed above is at the time of submission.

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