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Human Machine Teaming for Reduction of Operator Cognitive Load

Award Information
Agency: Department of Defense
Branch: Special Operations Command
Contract: 6SVL4-22-C-0014
Agency Tracking Number: S2D-0431
Amount: $1,224,894.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: SOCOM224-D004
Solicitation Number: 22.4
Solicitation Year: 2022
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-09-27
Award End Date (Contract End Date): 2023-09-30
Small Business Information
3600 Green Court Suite 600
Ann Arbor, MI 48105-1111
United States
DUNS: 009485124
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 (734) 709-7347
Business Contact
 Christian Thomas
Phone: (407) 437-4334
Research Institution

Special Operations Forces (SOF) Operators face high cognitive loads while performing various mission threads, including making complicated decisions and maintaining situation awareness in a dynamic battlespace. This can involve managing equipment (sensors and effectors), maintaining awareness of the environment, developing courses of action (COAs) that comply with rules of engagement (ROEs), and executing those COAs. These tasks increase cognitive load for an operator or unit among all the other tasks they are performing during a mission. An Artificial Intelligence-based Decision Support System (AI-DSS) can help offload some or all of these tasks to help reduce warfighter cognitive load. In prior work, SoarTech and Black River Systems have together developed a TRL 6 AI-DSS called AssistMATEā„¢ and demonstrated the feasibility of delegating multiple tasks. Specifically, AssistMATE focused on reducing cognitive load for counter-sUAS missions, allowing the operator to offload tasks including generating of ROE-compliant courses of action that cover multiple potential sensors and effectors (i.e., counter-UAS platforms) and multiple potential targets. In other work, SoarTech has demonstrated AssistMATE capabilities in a variety of domains such as managing multiple UxVs simultaneously and helping users perform procedure-oriented tasks. In each application, the focus has been on reducing cognitive load on the operators through the application of artificial intelligence-based decision support tools. In this project, our team proposes to adapt and extend these capabilities to SOCOM use cases and needs, such as pivoting to on-the-move operations, to reduce operator cognitive load, increase situation awareness (SA), and accelerate decision making and response times for mission accomplishment.

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

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