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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.

  1. Botnet Analytics Appliance (BNA)

    SBC: MILCORD LLC            Topic: HSB061008

    Recent reports indicate the activity of more than 6,000 botnet C and C servers. 70 million zombies are responsible for 80 percent of SPAM. Given the exponential growth of the botnet threat, the security of our nation s cyber infrastructure demand automated botnet activity monitoring solutions. In Phase I, Milcord developed a feasibility prototype of a Bayesian Activity Monitor for Botnet Defense. ...

    STTR Phase II 2007 Department of Homeland Security
  2. Development of Advanced Military Prosthetic Shoulder System

    SBC: Sarcos Group LC            Topic: A05161

    A 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
  3. Human Performance Optimization: Ketone Esters for Optimization of Operator Performance in Hypoxia

    SBC: HVMN Inc.            Topic: SOCOM17C001

    In 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
  4. Human Performance Optimization

    SBC: REJUVENATE BIO INC            Topic: SOCOM17C001

    Special 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
  5. System for Nighttime and Low-Light Face Recognition

    SBC: Systems & Technology Research LLC            Topic: SOCOM18A001

    Face 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
  6. Liquid cooled viscoelastic actuation for robust legged robot locomotion

    SBC: APPTRONIK INC            Topic: H601

    Apptronik 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
  7. Upper Body Addendum to Proposal S2-0328

    SBC: APPTRONIK INC            Topic: H601

    This 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
  8. Hybrid DNN-based Transfer Learning and CNN-based Supervised Learning for Object Recognition in Multi-modal Infrared Imagery

    SBC: TOYON RESEARCH CORPORATION            Topic: 1

    On 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
  9. Liquid-cooled actuation to achieve greater degrees of freedom and range of motion in untethered exoskeletons

    SBC: APPTRONIK INC            Topic: H6018135

    Apptronik 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
  10. Human-Machine Teaming with Machine Learning Algorithms

    SBC: KITWARE INC            Topic: SOCOM18B001

    Characterizing and understanding the interactions between human and machine plays an important role in extracting the most out of our machine learning algorithms while reducing human workload. We propose to develop a software prototype system that reduces user workload of exploiting AI algorithms for imagery exploitation. We will design a user-friendly system for content matching with interactive ...

    STTR Phase II 2020 Department of DefenseSpecial Operations Command
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