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Award Data
The Award database is continually updated throughout the year. As a result, data for FY23 is not expected to be complete until September, 2024.
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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Autonomous Swarming Hierarchies (ASH)
SBC: BOSTON FUSION CORP Topic: N23BT031Boston Fusion Corp. and the Cyber-Physical Systems Laboratory at Rutgers University propose Autonomous Swarming Hierarchies (ASH), a platform-agnostic multi-robot system (MRS) design software suite with three components: 1) a coordination module (CASH) that uses artificial intelligence/machine learning to automatically generate control policies for the robots comprising the system, 2) a networking ...
STTR Phase I 2023 Department of DefenseNavy -
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 -
Sensor Modality Translation through Contrastive Deep Learning
SBC: PHYSICAL SCIENCES INC. Topic: N23AT013Physical Sciences Inc. (PSI), in collaboration with the University of Rhode Island, proposes to develop an advanced algorithm suite for data translation across sensing modalities to support the development of automated target recognition and classification algorithms for Unmanned Underwater Vehicles. The proposed Deep Diffusion Sensor Translation (DDST) leverages recent advancements in generative ...
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 -
3D Printed Ablative Re-Entry Vehicle Heat Shields
SBC: MANTIS COMPOSITES INC Topic: DLA23A003Re-Entry Vehicles (RVs) are a critical component of the strategic weapon arsenal. While physics packages themselves have a substantial deterrence value, the ability to deliver those weapons quickly and with high survivability unlocks the ability to maintain a truly global deterrence. However, these thermal protection systems are encountering two developing challenges: Industrial Base Attrition: Th ...
STTR Phase I 2023 Department of DefenseDefense Logistics Agency -
Improved surface interface of OPF and PAN carbon fibers for Carbon-Carbon processing
SBC: ALKEMIX CORPORATION Topic: DLA23A003Specialized materials such as Carbon-Carbon (C-C) are required as primary structural and thermal protection elements to sustain the severe temperatures on the surface of Hypersonic Vehicles during high-speed flight. The C-C material currently qualified at Northrop in Hypersonic Glide-Bodies or “Aeroshells” consist of phenolic resin and a low fired, stretch broken polyacrylonitrile fiber (LFSP ...
STTR Phase I 2023 Department of DefenseDefense Logistics Agency -
Low Cost MLMI as a Hypersonic Aerostructure with TPS
SBC: Peregrine Falcon Corporation Topic: DLA23A003As Hypersonic weapons enter the US arsenal there is a need for cost control and high rate of production which is currently not being met by the current state of the art material systems, like Carbon-Carbon. What is needed is a Thermal Protection System (TPS) for aero structures that can survive the Hypersonic environments of high heat in oxygenated environments. A means to do this is using Peregr ...
STTR Phase I 2023 Department of DefenseDefense Logistics Agency