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Collective Meta-Reasoning Runtime Assurance of Machine Intelligence for Unmanned Autonomous Vehicles

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0104
Agency Tracking Number: N18B-032-0035
Amount: $124,927.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N18B-T032
Solicitation Number: 18.B
Timeline
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-17
Award End Date (Contract End Date): 2019-04-25
Small Business Information
1410 Sachem Place Suite 202
Charlottesville, VA 22901
United States
DUNS: 120839477
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Dr. John D. Schierman Dr. John D. Schierman
 Principal Research Scientist
 (434) 973-1215
 barron@bainet.com
Business Contact
 B. Eugene Parker, Jr.
Phone: (434) 973-1215
Email: barron@bainet.com
Research Institution
 University of Illinois at Urbana Champaign
 Susan A. Martinis Susan A. Martinis
 
Electrical and Computer Engineering 1901 S. First Street
Champaign, IL 61820
United States

 (217) 244-2405
 Nonprofit college or university
Abstract

Barron Associates has teamed with a prominent researcher in the field of formal verification of cyber physical systems to propose a new paradigm in runtime assurance for complex autonomous systems controlled and operated by artificial machine intelligence. A two-stage approach is considered in which formal verification processes are first performed offline at algorithm design time. Online, during operation, centralized and decentralized systems perform meta-reasoning of real-time decision processes to validate decision outcomes at a level greater than what each system can reason alone. This adds robustness to unanticipated missing information, communication dropouts, knowledge omissions, and potential malicious cyber-attacks. In Phase I, a challenge problem will be constructed to aid in the development of the proposed approach. A specific mission function will be identified as a technology demonstrator and the benefits of the approach will be proven in simulation.

* Information listed above is at the time of submission. *

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