You are here

Award Data

For best search results, use the search terms first and then apply the filters
Reset

The Award database is continually updated throughout the year. As a result, data for FY20 is not expected to be complete until September, 2021.

  1. Machine Learning and Data Fusion platform for Phenotype-based Pathogen Identification

    SBC: Triton Systems, Inc.            Topic: ST18C002

    Conventional methods for detecting pathogens, which are based on culturing the microorganism, are time-consuming and laborious. Machine learning provides an alternative path to identify pathogens using supervised learning algorithms. Most current computational tools utilize genomic or protein data to identify bacteria. These methods look for features in the whole genome that correlate to pathogeni ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  2. Station-keeping using Perception and Relative Image-based Navigation and Tracking (SPRINT)

    SBC: Scientific Systems Company Inc.            Topic: ST18C006

    SSCI and MIT propose to perform initial design and testing of an innovative tightly-coupled vison and GNC system for follower vehicles to achieve safe approach and station-keeping with the lead vehicle within some range tolerance and inside a 60 degree cone, under leader maneuvers and vehicle capability constraints. The resulting system is referred to as the SPRINT (Station-keeping using Perceptio ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  3. Visual Algorithms for Navigation and Guidance of UAVs with Autonomous Relational Decisions (VANGUARD)

    SBC: Charles River Analytics, Inc.            Topic: ST18C006

    Unmanned systems play a critical role in military operations across a wide range of missions. The DoD’s Unmanned Systems Integrated Roadmap identifies leader-follower tactics, swarming capabilities, sensor advancements, collision avoidance, and GPS-denied solutions as key technologies to support autonomy. Advances in these areas are needed to support coordinated multi-aircraft maneuvers and swar ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  4. StampPump: a Postage-Stamp Sized Autonomous Glycemic Control Mechanism for Patients Suffering Glycemic Abnormalities as a Result of Critical Illnesses

    SBC: Thermalin Inc.            Topic: ST18C004

    StampPump is a postage-stamp-sized (27x27x6 mm), fully-self-contained, closed-loop insulin patch pump system that is filled at the factory with enough insulin to treat a person with T1- or trauma-induced hyperglycemia for a full week. The device is shelf stable for at least 90 days and so is compatible with critical-care or forward deployment use. We propose to augment this system with the ability ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  5. Building an Autonomous Glycemic Control System for Hyperglycemia of Critical Illness

    SBC: Beta Bionics, Inc.            Topic: ST18C004

    It is well established that hyperglycemia of critical illness, general glucose intolerance, and insulin resistance are common among critically ill patients, including those without a diagnosis of diabetes mellitus upon hospital admission. Such glycemic dysregulation has been linked to increased patient morbidity and mortality, and longer recovery times. Furthermore, tight glycemic control has been ...

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  6. SBDUV APD/GPD detector arrays

    SBC: Radiation Monitoring Devices, Inc.            Topic: ST18C003

    The goal of the research is to provide a solar-blind, deep-UV photo-detector array that can be used in instruments detecting chemical and biological agents, such as TAC-BIO II, using UV Raman and Fluorescence measurements. The overall approach is to develop a solid-state detector array that achieves the performance goals for QE (>70%), gain (>1E6), dark current (

    STTR Phase I 2019 Department of DefenseDefense Advanced Research Projects Agency
  7. REsilience & Stability In DENse Terrains (RESIDENT)

    SBC: Boston Fusion Corp.            Topic: ST17C003

    Boston Fusion Corp. and Arizona State University will research and develop REsilience & Stability in DENse Terrains (RESIDENT), a multi-model, multi-scale framework for assessing indicators of stability and resilience in dense urban environments. Our team consists of subject matter experts in the Social and Computer Sciences providing the bedrock on which to build accurate mathematical models of u ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  8. STability and Resilience Analysis Technology for Urban Systems analysis (STRATUS)

    SBC: Systems & Technology Research LLC            Topic: ST17C003

    The unique scale, population density, complexity, and connectedness of megacities requires new tools for detecting and assessing risks related to civil unrest, rule of law, terrorism, and other sources of instability, and for understanding the underlying dynamics. In addition, gray zone operations pose a new and strategically important class of threats to the stability of nation states and cities ...

    STTR Phase I 2018 Department of DefenseDefense Advanced Research Projects Agency
  9. Optimizing Human-Automation Team Workload through a Non-Invasive Detection System

    SBC: SONALYSTS, INC.            Topic: ST16C003

    In this project, Sonalysts will team with the University of North Dakota to establish the feasibility of a deployable, unobtrusive suite of sensors and data processing approaches collectively known as Cognitively-Oriented Physiological Indicators of Load, Operational performance, and Tension (CO-PILOT). CO-PILOT will provide real-time indicators of operator state that can be used to inform adaptiv ...

    STTR Phase I 2017 Department of DefenseDefense Advanced Research Projects Agency
  10. Automation Support using non-Invasive Measures of Operator Vocalization (ASIMOV)

    SBC: Charles River Analytics, Inc.            Topic: ST16C003

    Human-machine teams are increasingly prevalent across the DoD. These teams unite human operators with advanced automated teammates to execute complex, mission-critical tasks. Unfortunately, this collaboration between automated and human teammates can increase operator strain, because operators must complete their own tasks while also monitoring teammates and distributing tasks; one specific strain ...

    STTR Phase I 2017 Department of DefenseDefense Advanced Research Projects Agency
US Flag An Official Website of the United States Government