SBIR/STTR Research Award

STE LTE Autonomous Adaptive Networks

Award identifier 9cd74ce76f4a707c6b2eaea1e413c3ab8ac0adc10e3ff0f454e6ca7578451ea8Awarding agency Department of Defense · Army

Award amount

$111,458

Program and phase

SBIR · Phase I

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Defense
Branch
Army
Recipient company
TITENN INC
Proposal award date
2020-06-26
Contract end date
2021-06-14
UEI
MTJBDKWK9MX6
Solicitation number
20.1
Topic code
A20-083

Research abstract

The Army’s future vision is to have a “high-fidelity replication/representation of real combat to include direct and indirect fire weapons and non-lethal fires. Also, to conduct live training in conjunction with immersive (live-mixed reality and constructive) training enabling units, all over the world, to train together, improving multi-echelon training exercises. Most importantly to be able to conduct tough, iterative, dynamic, and realistic multi-echelon combined arms maneuver and mission command training in support of Multi-Domain Operations.” - from Synthetic Training Environment (STE) Live Training Environment (LTE) Statement of Need (SoN). Being able to use immersive live-mixed reality, such as Augmented Reality (AR) Head-Mounted Displays (HMD) at the Point of Need, is essential to implementing the Army’s vision. AR HMDs provide deployed soldiers with a more immersive training capability, such as realistic representations of real combat environments where soldiers can visualize direct and indirect fired weapons munitions, non-lethal fire effects, and much more. However, there are several challenges, such as bandwidth and latency, to implementing AR HMDs in Live Training immersive live-mixed reality environments across Home Stations (HSs), Combat Training Centers (CTCs), and deployed locations.   To solve the bandwidth and latency challenges, TITENN is proposing to develop an Autonomous Adaptive Network (AAN).   AAN is a game-changing technology for the Army and will address core challenges with using AR HMDs to support STE LTE’s vision, which operates in a decoupled cloud simulation environment supporting real-time AI processing. AAN enables true replication/representation of real combat to include Direct and Indirect Fire weapons, non-lethal fires, as well as culturally-specific human behaviors, autonomous civilians, and military equipment behaviors (robots, drones, droids, etc.).  AAN also facilitates offloading computationally expensive processing into the cloud.  AAN’s low latency concept also advances current security models enabling a high-performance synthetic environment to meet complex requirements for training and integration of STE LTE’s ecosystem

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

2 SBIR/STTR records share this UEI (2019–2020). Reported award amounts total $161,444. Reported amounts are not federal obligations.

Phases: Phase I

Agencies: Department of Defense

Agency intelligence

Department of Defense

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.