Advanced Verification Toolset for Learning-Based UAS Operating in Uncertain Environments

Award Information
Agency: Department of Defense
Branch: Office of the Secretary of Defense
Contract: FA8650-14-M-2454
Agency Tracking Number: O133-HS2-1038
Amount: $149,985.00
Phase: Phase I
Program: SBIR
Awards Year: 2014
Solitcitation Year: 2013
Solitcitation Topic Code: OSD13-HS2
Solitcitation Number: 2013.3
Small Business Information
Aurora Flight Sciences Corporation
9950 Wakeman Drive, Manassas, VA, 20110-
Duns: 604717165
Hubzone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Sacin Jain
 Sr. GNC Engineer
 (617) 229-6812
 sjain@aurora.aero
Business Contact
 Scott Hart
Title: Financial Analyst
Phone: (617) 500-4892
Email: shart@aurora.aero
Research Institution
N/A
Abstract
This effort proposes to develop a toolset to evaluate the effectiveness of a safety-controller that monitors a learning-based autonomous control system. The traditional use of deterministic verification techniques for real-time monitoring is not feasible in the presence of uncertainty. This effort would advance the recommended verification techniques to include non-deterministic approaches. The output would be to develop a Mathworks-based toolset to evaluate the run-time safety controller using advanced verification techniques. The inputs to the tool would allow for unexpected / unknown inputs into the system under test to better reflect real world conditions. The effort increases the fidelity of the verification technique and evaluates a learning-based trajectory planner with a safety controller currently used to operate a helicopter. This effort examines the use of boundary certificates and other approaches to further improve the detection of issues that traverse a safety boundary.

* information listed above is at the time of submission.

Agency Micro-sites

US Flag An Official Website of the United States Government