Automated Modeling and Simulation Tool for Lightening the Load of Warfighters

Award Information
Agency:
Department of Defense
Branch
Navy
Amount:
$69,970.00
Award Year:
2008
Program:
STTR
Phase:
Phase I
Contract:
N00014-08-M-0272
Award Id:
85164
Agency Tracking Number:
N08A-019-0299
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Oakdale Research Campus, Iowa City, IA, 52242
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
149037256
Principal Investigator:
Karim Abdel-Malek
Director, CCAD
(319) 335-5676
amalek@engineering.uiowa.edu
Business Contact:
Rich Lineback
VP, Engineering
(319) 335-5723
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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