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Award Data
The Award database is continually updated throughout the year. As a result, data for FY22 is not expected to be complete until September, 2023.
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.
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Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia
SBC: HVMN Inc. Topic: SOCOM17C001In the setting of altitude-induced hypoxia, operator cognitive capacity degrades and can compromise both individual and team performance. This degradation is linked to falling brain energy (ATP) levels and an increased reliance on anaerobic energy production from glucose. Ketone bodies are the evolutionary alternative substrate to glucose for brain metabolic requirements; previous studies have sho ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Human Performance Optimization
SBC: REJUVENATE BIO INC Topic: SOCOM17C001Special Operations Forces (SOF) are an integral aspect of the US military. SOF operators are among the most elite and highly qualified individuals in the U.S. military. As such, extraordinary physical and mental demands are placed upon them to excel in extreme environments for extended periods of time. This unrelenting cycle of combat deployments and intense pre-deployment training shortens the fu ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery
SBC: TOYON RESEARCH CORPORATION Topic: 1On this effort Toyon Research Corp. and The Pennsylvania State University are developing deep learning-based algorithms for object recognition and new class discovery in look-down infrared (IR) imagery. Our approach involves the development of a hybrid classifier that exploits both transfer learning and semi-supervised paradigms in order to maintain good generalization accuracy, especially when li ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
Algorithms for Look-down Infrared Target Exploitation
SBC: Signature Research, Inc. Topic: 1Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...
STTR Phase I 2018 Department of DefenseNational Geospatial-Intelligence Agency -
System for Nighttime and Low-Light Face Recognition
SBC: Systems & Technology Research LLC Topic: SOCOM18A001Face recognition performance using deep learning has seen dramatic improvements in recent years. This improvement has been fueled in part by the curation of large labeled training datasets with millions of images of hundreds of thousands of subjects.This results in effective generalization for matching over pose, illumination, expression and age variation, however these datasets have traditionally ...
STTR Phase I 2018 Department of DefenseSpecial Operations Command -
Development of Advanced Military Prosthetic Shoulder System
SBC: Sarcos Group LC Topic: A05161A new dual pump hydraulic supply designed to enable energetically autonomous exoskeleton robots will be developed, tested and demonstrated. This new hydraulic supply will be integrated with a high performance hydraulically actuated full body exoskeleton robot and used to test and demonstrate the overall performances of such systems. New control policies that include: (i) an assist mode, where the ...
STTR Phase II 2017 Department of DefenseSpecial Operations Command -
Liquid cooled viscoelastic actuation for robust legged robot locomotion
SBC: APPTRONIK INC Topic: H601Apptronik Systems in cooperation with the University of Texass Human Centered Robotics Lab (HCRL), Carnegie Mellon Universitys Robotics Institute and Italys National Research Institute (CNR), will collaborate to develop a new type of exoskeleton that is founded upon Apptroniks Visco-Elastic Liquid Cooled Actuator (VLCA). The fundamental goal of this program is the development of a powered exoskel ...
STTR Phase II 2017 Department of DefenseSpecial Operations Command -
Upper Body Addendum to Proposal S2-0328
SBC: APPTRONIK INC Topic: H601This is an Addendum to previously submitted proposal that includes the addition of a powered upper body portion of an exoskeleton. In this addendum we propose the additional requirements of researching, fabricating and integrating a powered upper body to the previously outlined lower body. These two systems together will comprise the entire exoskeleton proposed by the contractor. Through this ...
STTR Phase II 2017 Department of DefenseSpecial Operations Command -
Liquid-cooled actuation to achieve greater degrees of freedom and range of motion in untethered exoskeletons
SBC: APPTRONIK INC Topic: H6018135Apptronik Systems Inc., in cooperation with the University of Texas Human Centered Robotics Lab (HCRL) and Huston-Tillotson University Robotics Lab (a historically black college and university HBCU), endeavor to advance the movement capabilities and modularity of the exoskeleton being developed under contract #H92222-17-C-0050. The primary goal of this program is to optimize the range of movement ...
STTR Phase II 2017 Department of DefenseSpecial Operations Command