Model Driven Autonomous System Demonstration and Experimentation Workbench
Award last edited on: 7/23/2013

Sponsored Program
Awarding Agency
Total Award Amount
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Solicitation Topic Code
Principal Investigator
William Smuda

Company Information

Adept Analytics LLC

1353 Forbes Drive
Bloomfield Hills, MI 48302
   (248) 496-6278
Location: Single
Congr. District: 09
County: Oakland

Phase I

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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.

Robotics, Autonomy, Machine Intelligence, Feature Modeling, Model Driven Architecture, Model Driven Design, Domain Specific Language, System Analysis

Phase II

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