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

Award Information

Department of Defense
Office of the Secretary of Defense
Award ID:
Program Year/Program:
2014 / SBIR
Agency Tracking Number:
Solicitation Year:
Solicitation Topic Code:
Solicitation Number:
Small Business Information
9950 WAKEMAN DR MANASSAS, VA 20110-2702
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Phase 1
Fiscal Year: 2014
Title: Advanced Verification Toolset for Learning-Based UAS Operating in Uncertain Environments
Agency / Branch: DOD / OSD
Contract: FA8650-14-M-2454
Award Amount: $149,985.00


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.

Principal Investigator:

Sacin Jain
Sr. GNC Engineer
(617) 229-6812

Business Contact:

Scott Hart
Financial Analyst
(617) 500-4892
Small Business Information at Submission:

Aurora Flight Sciences Corporation
9950 Wakeman Drive Manassas, VA 20110-

EIN/Tax ID: 541502935
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No