Model Driven Autonomous System Demonstration and Experimentation Workbench

Award Information
Agency:
Department of Defense
Amount:
$149,999.00
Program:
SBIR
Contract:
HDTRA1-13-P-0016
Solitcitation Year:
2012
Solicitation Number:
2012.3
Branch:
Defense Threat Reduction Agency
Award Year:
2013
Phase:
Phase I
Agency Tracking Number:
O123-AU2-5002
Solicitation Topic Code:
OSD12-AU2
Small Business Information
Adept Analytics, LLC
1353 Forbes Dr., Bloomfield Hills, MI, -
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
969847834
Principal Investigator
 William Smuda
 Principle Investigator
 (248) 496-6278
 bill.smuda@adept-analytics.com
Business Contact
 William Smuda
Title: owner
Phone: (248) 496-6278
Email: bill.smuda@adept-analytics.com
Research Institution
 Stub
Abstract
To achieve high-level strategic goals, DoD elements are investigating the potential of adding autonomy to unmanned assets. An autonomous system must be able to amend its"pre-loaded"plan by rapidly assessing the current situation, examining a number of possible outcomes, initiating a course of action and continuing to reassess its decisions and plan. Currently, data needed for training autonomous models, as well as response algorithms and heuristics, are limited for the system architect designing an autonomous platform. In areas where such data is available, such as observations of the recent DARPA Grand Challenge for autonomous automobiles, no well-developed system for identifying, archiving and maintaining useful information related to autonomous platform design exists. A well-defined framework for Autonomous Demonstration and Experimentation could collect real-world data, design decisions, requirements and experiment results into a scalable and intuitive workbench. This workbench will greatly aid the design of autonomous systems and identify gaps as well as provide management with actionable data.

* information listed above is at the time of submission.

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