SBIR/STTR Research Award

Highly Autonomous Adaptation for UAVs

Award identifier 84ed2df6154dbb7b9ae976beedb58bc7303c40ff6a169eadced7684bc7851fc4Awarding agency Department of Defense · Navy

Award amount

$139,994

Program and phase

SBIR · Phase I

Award year

2019

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Award details

Awarding agency
Department of Defense
Branch
Navy
Recipient company
UTOPIACOMPRESSION,CORPORATION
Proposal award date
2019-09-17
Contract end date
2020-03-24
UEI
HR7PGAJ92Z97
Solicitation number
19.2
Topic code
N192-062

Research abstract

UAVs tasked in complex, uncertain environments need the ability to act dynamically and autonomously to changing conditions. Deep reinforcement learning can play a critical role in the decision making process, melding the mission/tasking parameters, scene understanding, and human-in-the-loop inputs for intelligent autonomous navigation that is robust in the face of latency, broken communication, and threats. UtopiaCompression proposes to use the latest advances in deep learning, including reinforcement learning, to support the DoD in this mission.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

121 SBIR/STTR records share this UEI (2004–2025). Reported award amounts total $42,524,603. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, Department of Homeland Security, National Aeronautics and Space Administration, National Science Foundation, Department of Energy

Agency intelligence

Department of Defense

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