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Scientific Systems Company Inc. STTR Phase II Award, April 2020

A STTR Phase II contract was awarded to Scientific Systems Company Inc. in April, 2020 for $747,599.0 USD from the U.S. Department of Defense and United States Navy.

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Contents

sbir.gov/node/1927795
Is a
SBIR/STTR Awards
SBIR/STTR Awards

SBIR/STTR Award attributes

SBIR/STTR Award Recipient
Scientific Systems Company Inc.
Scientific Systems Company Inc.
0
Government Agency
U.S. Department of Defense
U.S. Department of Defense
0
Government Branch
United States Navy
United States Navy
0
Award Type
STTR0
Contract Number (US Government)
N68335-20-C-02310
Award Phase
Phase II0
Award Amount (USD)
747,5990
Date Awarded
April 16, 2020
0
End Date
October 18, 2021
0
Abstract

SSCI and MIT (Prof. Julie Shah) propose to develop and test a system that provides real-time assurance and trust in decisions made by autonomous collaborating vehicles. The proposed system is referred to as the RESTORE (Robust Execution System for Trusted Operation in Relevant Environments) and represents a decision support tool which facilitates decision making by the operator in cases when decisions by the Collaborative Autonomy (CA) system results in deviations from mission objectives. Key elements of RESTORE Include: (i) Contextual Interrogation Engine which uses an innovative approach to contextualize the interrogation, present the results in natural language, and increase trust in autonomy; (ii) Dynamic assurance engine which monitors mission parameters during operation and, in the case of deviations, provides the operator with alternate courses of action; and (iii) Vehicle-agnostic middleware to enable applicability of RESTORE to heterogeneous platforms operating in different domains. RESTORE will extend our field-proven CA system and MIT’s autonomy interrogation techniques with results presented in natural language. SSCI’s expertise in the development, implementation and transition of CA systems to operational platforms, combined with MIT’s expertise in machine intelligence and human-machine teaming, will result in an enhanced capability applicable to a range of DoD programs and platforms.

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