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DARPA's REMA (Rapid Experimental Missionized Autonomy) program enhances commercially available and stock military drones by adding an autonomy subsystem that increases the drone's capability and renders ineffective adversaries' electromagnetic countermeasures that disrupt operator-drone communication.
The single-phase program develops a drone-autonomy adapter interface and mission-specific autonomy software, utilizing accelerating development spirals for tactical deployment. Focus areas include onboard AI inference for navigation, target recognition, and mission continuation in GPS-denied and jammed environments; foundation models for tactical autonomy; and modular autonomy stacks compatible with diverse commercial drone platforms.
Managed by DARPA TTO under PM Phillip Smith.
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Or search similar grants →According to the current listing, eligibility includes: Open to U.S. industry, academic institutions, FFRDCs, and small businesses with relevant capabilities. International partners may participate subject to ITAR/export control. Performers selected via DARPA TTO solicitations and BAA calls. Confirm the full requirements in the official notice before applying.
The current listing shows multi-million dollar performer awards. Program budget approximately USD 13,800,000 in FY2025 with continuation funding. Individual awards typically USD 1,000,000 to USD 8,000,000 per performer. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for DARPA REMA Rapid Experimental Missionized Autonomy for Converting Commercial Drones into AI-Enabled Autonomous Combat Platforms are due December 31, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
DARPA REMA Rapid Experimental Missionized Autonomy for Converting Commercial Drones into AI-Enabled Autonomous Combat Platforms is funded by Defense Advanced Research Projects Agency (DARPA) Tactical Technology Office (TTO). Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
AFRL's Geospatial Intelligence Processing and Exploitation (GeoPEX) BAA seeks white papers for research, development, integration, test and evaluation of technologies and techniques to provide geospatial intelligence (GEOINT) in all its forms and from whatever source — imagery, imagery intelligence, or geospatial data and information. The open, two-step BAA prioritizes AI-enabled sensor fusion, machine learning for imagery exploitation, multi-source data integration, autonomous geospatial reasoning, and intelligent processing pipelines. Total funding approximately $99.9M with individual awards typically $250K to $10M over up to 24 months. White papers accepted on a rolling basis until September 30, 2026; formal proposals are by invitation only.
The U.S. Army's SBIR/STTR Artificial Intelligence/Machine Learning Open Topic provides non-dilutive funding to small businesses developing AI and machine learning solutions for defense applications such as supply chain management, logistics coordination, target identification, and modeling and simulation. Awards follow the standard SBIR/STTR structure: Phase I establishes technical feasibility (typically up to about $250,000) and Phase II funds development and demonstration (typically up to about $2,000,000), with Phase III for commercialization. Open-topic solicitations accept proposals on a periodic basis.
DARPA's TIAMAT (Transfer from Imprecise and Abstract Models to Autonomous Technologies) program develops sim-to-real transfer techniques that train autonomous systems in low-fidelity, abstract simulations and reliably deploy them in unpredictable physical environments. Research targets foundations for rapid sim-to-real generalization, robustness to physics-model error, and transfer learning across morphology and sensor configurations. The program is structured as two 18-month phases and supports applications including ground autonomy, aerial autonomy, and robotic manipulation in adversarial, novel, or contested settings. Awards have included University of Central Florida ($1.2M) and other academic and industry performers. TIAMAT is a core DARPA investment in foundational autonomy R&D.
MTO opened six SBIR topics on May 27 with a single June 24 close: nanopore proteomics, compact wideband tunable RF filters, 800°C-rated integrated circuits, passive thermal spreaders, radiation-hardened codesign, and low-resource computing for legacy hardware reuse. Together they map the office's bet on where U.S. semiconductor advantage gets reasserted — and which small businesses get to ride along.
Read articleDARPA MTO opened six FY26 SBIR topics on May 27 with a June 24 deadline — nanopore proteomics, compact RF filters, 800°C ICs, passive thermal spreaders, radiation-hardened codesign, and low-resource computing. The topics read like a wishlist for the next decade of contested-environment microelectronics. Here is what each one is actually asking for, and how small businesses should triage the four-week window.
Read articleThe Hewlett Foundation's Emerging Technology and Security Initiative commits $20 million a year through 2031 across AI, biotechnology, and quantum computing security. Its 2026 exploratory grants went to thirteen named institutions with no open call. For organizations outside that list, the path in runs through a specific set of moves — and the five-year term starting in 2027 is the window.
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