Allows small businesses to submit to Direct to Phase II applications if they performed the Phase I research through other funding sources.
The objective of this SBIR topic is to advance methods for generating and labeling synthetic data representing various classes of Radio Frequency (RF) signals. This synthetic data will support the training of Electronic Support and Signals Intelligence (SIGINT) models aimed at enhancing automated detection, characterization, and identification (DCI) of Signals of Interest (SoI).
The Aerial Delivery field has a systemic shortage of personnel at Skill Level 1 positions across all COMPOS that places the mission of packing personnel parachutes, large cargo parachutes, and rigging of equipment at risk of mission failure. This topic aims to deliver wearable, augmented reality and/or computer vision devices to non-Parachute Rigger Soldiers to increase technical capabilities for rigging their unit organic equipment, thus reducing overall Army Parachute Rigger requirements.
Equipment Rigging with Augmented Reality / Computer Vision Read More »
The objective of this research topic is to explore Boyd’s Observe, Orient, Decide and Act Loop with the goal of finding disruptive courses of action in a multi-domain environment that allow warfighters to impact both the rate of engagement with a competitor, but also the rhythm of engagement that allow our commanders and warfighters to leverage both the complexity and dynamism inherent in a multi-domain operation to create decisive wins through strategic surprise.
Large Language Model Course of Action Analysis Read More »
The proposed SBIR topic aims to advance the capabilities of large language models by addressing critical challenges and enhancing functionalities relevant to military applications, particularly within the U.S. Army.
Dynamic Generative Large Language Model for Continuous Situational Awareness Read More »
This open topic accepts both Phase I and Direct to Phase II submissions. Phase I proposals are accepted for a cost up to $250,000 for a 6-month period of performance and Direct to Phase II proposals are accepted for a cost up to $2,000,000 for a 24-month period of performance.
Battery Focused Open Topic Read More »
This topic accepts Direct to Phase II proposals submissions for a cost up to $2,000,000 for a 24-month period of performance.
Affordable Alane Fuel Read More »
This open topic accepts both Phase I and Direct to Phase II submissions. Phase I proposals are accepted for a cost up to $250,000 for a 6-month period of performance and Direct to Phase II proposals are accepted for a cost up to $2,000,000 for a 24-month period of performance. All submissions most address the following 6 AI sub-fields: Synthetic data generation in a format applicable to a given situation that is not obtained by direct measurement. This includes visual, textual, video, geospatial, and sensor data.
Artificial Intelligence/ Machine Learning (AI/ML) Focused Open Topic Read More »
This open topic accepts both Phase I and Direct to Phase 2 submissions. All submissions most address the following 6 sub-fields
Hybrid Electric Powertrain, Power and Propulsion Systems (HEPPS) Open Topic Read More »
This Army SBIR solicitation is for artificial intelligence and machine learning-driven methodologies that can control the production processes for Nano-Nitramines. The Army seeks to produce the most efficient, effective formulations currently known in an agile and flexible manner. AI/ML-driven manufacturing and formulation science can apply “cradle to grave” for Nano-Nitramines, and can enable their widespread adoption by making research and production automated.
AI-Driven Production of Coarse- and Nano-Nitramines Read More »
With the increasing availability of digital imagery, including satellite data for electro-optical/infrared, synthetic aperture radar and full-motion video, there is a growing need for automated methods to efficiently process and analyze vast amounts of multi-modal data.
Robust Computer Vision for Better Object Detection with Limited Training Data Read More »
