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Artificial Intelligence and Machine Learning-Based Autonomous Mission Planning for Intelligence, Surveillance, and Reconnaissance (ISR) Missions -- 21

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-22-C-0178
Agency Tracking Number: N21B-T021-0033
Amount: $139,947.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N21B-T021
Solicitation Number: 21.B
Timeline
Solicitation Year: 2021
Award Year: 2022
Award Start Date (Proposal Award Date): 2022-01-11
Award End Date (Contract End Date): 2022-07-27
Small Business Information
1818 Library Street Suite 600
Reston, VA 20190-1111
United States
DUNS: 107939233
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 John Asplund
 (703) 787-7800
 asplund@metsci.com
Business Contact
 Erin Augustyniak
Phone: (703) 326-2870
Email: augustyniak@metsci.com
Research Institution
 University of Maryland, College Park
 Danette Boone
 
7809 Regents Drive
College Park, MD 20742-5141
United States

 (301) 405-8108
 Nonprofit College or University
Abstract

Metron, Inc. and the Maryland Robotics Center (MRC) at the University of Maryland propose to design autonomous, distributed ISR mission planning algorithms deployed on UAV platforms that can replan dynamically based on environmental and mission-specific changes. Agents will negotiate UAV tasks dynamically using AI market-based consensus in which global objectives emerge naturally from UAVs pursuing local goals. Agents will execute UAV routing and control through Bayesian inference and model-based policies that select actions given state based on maximizing value, similar to the role of Q-functions in reinforcement learning. The key challenges are to design algorithms that are distributed, operate in real-time with onboard hardware, address environmental and operational characteristics, and make good, well-informed decisions that are sufficiently interpretable to gain the trust of an operator. We organize our technical system design requirements into three main components: initial mission planning, UAV routing and control, and dynamic replanning.

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

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