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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.
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.
The ARM Institute's 26-01 Core-Funded Technology Project Call makes approximately $2 million available to fund multiple robotics and AI projects that advance U.S. manufacturing, with individual requests to the ARM Institute capped at $500,000. Topic areas are multi-modal inputs for AI robotics in manufacturing, rapid re-tasking and robot agility, multi-robot and multi-human collaboration with supervised autonomy, adaptive real-time path planning and control, and mobile robotics. The call is oriented toward Department of Defense manufacturing needs including castings, forgings, submarines, unmanned aerial systems, and munitions production. Concept papers are due February 4 in the ARM Member Community, with a public informational webinar January 8 and a target project start date of October 1, 2026. Project cost share is weighted in evaluation.
DARPA's TIAMAT (Transfer from Imprecise and Abstract Models to Autonomous Technologies) program tackles the sim-to-real transfer problem in robotics and autonomous systems by training autonomous systems in low-fidelity simulations and then transferring that learned behavior into the real world. The program addresses one of the central barriers to deploying autonomous ground vehicles and other robotic systems at military scale: the cost and brittleness of training in high-fidelity simulation or live environments. TIAMAT is structured around two 18-month phases that move from foundational sim-to-real algorithm research to integrated demonstrations on physical platforms. The program supports a small number of high-performing teams of universities, defense contractors, and small businesses developing the next generation of robust autonomy for ground, aerial, and maritime applications.
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 articleArtists Make Technology named its first 20 grantees on October 28, 2026: $2.75 million in grants of up to $150,000, chosen from 392 applications (a 5.1% success rate). The three-year, $11 million initiative plans up to 40 grants, so roughly half are still to come. What the first cohort shows about what wins, and how to prepare for the next call.
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