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Decision Support for Operators of Fully Autonomous Systems using RESTORE: Robust Execution System for Trusted Operation in Relevant Environments

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0105
Agency Tracking Number: N18B-032-0034
Amount: $124,839.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N18B-T032
Solicitation Number: 18.B
Solicitation Year: 2018
Award Year: 2019
Award Start Date (Proposal Award Date): 2018-10-17
Award End Date (Contract End Date): 2020-01-27
Small Business Information
500 West Cummings Park Suite 3000
Woburn, MA 01801
United States
DUNS: 859244204
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Dr. Jovan Boskovic Dr. Jovan Boskovic
 Principal Research Engineer II
 (781) 933-5355
Business Contact
 Lora Loyall
Phone: (781) 933-5355
Research Institution
 Massachusetts Institute of Technology
 Jei Lee Freeman Jei Lee Freeman
77 Massachusetts Avenue Building NE18-901
Cambridge, MA 02139
United States

 (617) 253-1695
 Nonprofit College or University

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 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. RESTORE has the following key elements: (i) Contextual Interrogation Engine which uses an innovative approach to contextualize the interrogation 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 which enables RESTORE to work with CA systems employing heterogeneous platforms operating in different domains. RESTORE will extend our field-proven CA system which has been demonstrated through in-water tests with 40 collaborating UUVs under the DARPA CNAV Program. SSCI is one of the leaders in development, implementation and transition of CA systems to operational platforms. This, 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.

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

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