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Award Data
The Award database is continually updated throughout the year. As a result, data for FY24 is not expected to be complete until March, 2025.
Download all SBIR.gov award data either with award abstracts (290MB)
or without award abstracts (65MB).
A data dictionary and additional information is located on the Data Resource Page. Files are refreshed monthly.
The SBIR.gov award data files now contain the required fields to calculate award timeliness for individual awards or for an agency or branch. Additional information on calculating award timeliness is available on the Data Resource Page.
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Deep Reinforcement Learning for Collaborative Multi-Robot Systems with Low-Latency Wireless Networking
SBC: TIAMI LLC Topic: N23BT031In this Phase I effort, Tiami, LLC, aims to develop and demonstrate a hardware proof of concept for a collaborative multi-robot system (MRS) that leverages imitative augmented deep reinforcement learning (IADRL) amongst heterogeneous uncrewed systems (robots) to achieve a common task. Collaboration is based on low-latency machine-to-machine wireless links between robots that use both RF and optica ...
STTR Phase I 2023 Department of DefenseNavy -
Ad Hoc Swarm Modulation and Adaptation
SBC: IOTAI INC Topic: N23BT031Ad Hoc Swarm Modulation and Adaptation focuses on the ability to enable secure cyber communications, data, and distributed AI processing for any robotic swarm in any condition. The system incorporates a range of multi-robotic system functionality to allow for coordination, cooperation, and reconfigurable methods of robotic teams, flocks, and swarms. The system further includes methods for swar ...
STTR Phase I 2023 Department of DefenseNavy -
AI-Based Learning Environment (ABLE) for Undersea Warfare (USW) Training
SBC: PACIFIC SCIENCE & ENGINEERING GROUP, INC. Topic: N23AT014To compete on the world stage of undersea warfare (USW), the US Navy’s USW systems are frequently updated with advanced capabilities. As a result, modernization trainers need to perform the challenging tasks of updating training material to reflect the new (and obsolete) capabilities. This process requires comparing legacy to updated documentation, identifying changes to system capabilities, and ...
STTR Phase I 2023 Department of DefenseNavy -
UUV Sensor Transformation
SBC: Arete Associates Topic: N23AT013Areté and its teaming partner the University of Arizona (UofA) will develop a software tool that transforms sensor and metadata from a given sensor system into realistic synthetic data as if it were collected by a different sensor system. The exponential rise in available data from a multitude of sensor systems has driven commercial and academic entities to achieve significant innovations in arti ...
STTR Phase I 2023 Department of DefenseNavy -
Realistic UUV Data Transformation Tool
SBC: MAKAI OCEAN ENGINEERING INC Topic: N23AT013Undersea target recognition from sensor systems onboard unmanned underwater vehicles (UUVs) play a critical role in the US Naval strategies and mission capabilities. Machine Learning provides a game-changing opportunity for improved Automated Target Recognition (ATR), but current attempts remain limited due to a lack of adequate training data. ML-based ATR algorithms are statistics-based systems; ...
STTR Phase I 2023 Department of DefenseNavy -
Time Resolved Multiparameter Flow Diagnostic for Engine Exhaust Plumes
SBC: METROLASER, INCORPORATED Topic: N23AT005High temperature jet plumes emanating from aircraft engines and missiles produce effects that are of interest for threat detection, environmental noise, and engine development purposes. Optical and infrared emissions from plumes are sources of light and heat signatures, respectively, that can potentially be used for tracking or targeting vehicles in flight. Acoustic noise from jet plumes can pot ...
STTR Phase I 2023 Department of DefenseNavy -
Improved High-Frequency Bottom Loss Characterization
SBC: HEAT, LIGHT, AND SOUND RESEARCH, INC. Topic: N17AT026The existing HFBL (High-Frequency Bottom Loss) database has been recognized to be unsatisfactory due to its lack of physical underpinning and inability to provide consistent performance across frequency and space. The aim of the project is to replace the HFBL database with a geoacoustic model that leads to a smooth transition to the LFBL (Low-Frequency Bottom Loss) model at 1 kHz. To this end, thi ...
STTR Phase II 2023 Department of DefenseNavy -
Data-Driven Hypersonic Turbulence Modeling Toolset
SBC: ATA ENGINEERING, INC. Topic: N22AT016Development of hypersonic aircraft and weapon systems has become a critical focus for the Department of Defense to maintain global strike and projection of force capabilities. Despite decades of research, traditional computational fluid dynamics (CFD) methods are either incapable of adequately predicting complex features in hypersonic flows or too expensive to be of practical use for vehicle desig ...
STTR Phase II 2024 Department of DefenseNavy -
Compact Condensers Enabled by Print-to-Cast Additive Manufacturing
SBC: ERG Aerospace Corporation Topic: N23AT024High power electronics are being increasingly limited by conventional single-phase thermal management technologies. Refrigerant two-phase cooling presents a significant opportunity for thermal management of high-power electronics. While recent advances in cold plates and evaporators have been demonstrated in high heat flux applications, the condenser-side of the two-phase coolant loop has not kept ...
STTR Phase I 2023 Department of DefenseNavy -
Compact Condensers Enabled by Additive Manufacturing
SBC: WECOSO, INC. Topic: N23AT024Thermal management using two-phase cooling systems offers significant advantages in terms of size, weight, and power reduction. These size reductions are mainly attributable to the evaporation part of the process, where heat transfer coefficients can be as high as 100 kW m-2 K-1. This is not the case for condensation, which can typically transfer lower heat fluxes at the same temperature differenc ...
STTR Phase I 2023 Department of DefenseNavy