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Air Force SBIR DAF26BZ03-DV020 AI-Driven Humanoid Robotic Fleet Management for Aircraft Maintenance and Sustainment is sponsored by U.S. Department of the Air Force (AFWERX SBIR). Air Force SBIR topic DAF26BZ03-DV020 seeks advanced AI-driven solutions for a scalable fleet management platform coordinating humanoid, mobile, and industrial robots performing aircraft maintenance and sustainment.
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Air Force SBIR: Humanoid Robot Fleet Management for Aircraft Maintenance and Sustainment — BW&CO Humanoid Robotic Fleet Management - SBIR Topic DAF26BZ03-DV020 Active specific topic DSIP The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items.
Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 3. 5 of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
To Effectively and Efficiently Coordinate Multiple Humanoid and Industrial Robots for Complex Tasks in Dynamic Industrial Environments The technology within this topic is restricted under the International Traffic in Arms Regulation (ITAR), 22 CFR Parts 120-130, which controls the export and import of defense-related material and services, including export of sensitive technical data, or the Export Administration Regulation (EAR), 15 CFR Parts 730-774, which controls dual use items.
Offerors must disclose any proposed use of foreign nationals (FNs), their country(ies) of origin, the type of visa or work permit possessed, and the statement of work (SOW) tasks intended for accomplishment by the FN(s) in accordance with section 3. 5 of the Announcement. Offerors are advised foreign nationals proposed to perform on this topic may be restricted due to the technical data under US Export Control Laws.
Within Air Force depots for aircraft maintenance and sustainment, there are many workloads that present significant challenges for human personnel due to reasons including high physical demand, repetitive tasks, and unfriendly environmental conditions.
In the endeavor of optimizing manufacturing and sustainment operations, robots have increasingly been integrated, serving to separate human personnel from potentially hazardous activities and creating opportunities for process improvement. The robots that have been determined to be most versatile in industrial settings as support to human personnel are those designed to operate similarly, in a humanoid manner.
As the potential of humanoid robots for widespread deployment in various applications is growing in accordance with their increasing sophistication and capability, so is the cruciality of managing and coordinating large fleets of these robots effectively for the maximization of their utility and the assurance to complete tasks successfully.
While implementing a fleet management system allows for the dynamic allocation of robots to specific maintenance tasks based on real-time demand and priority, resource utilization optimization, and aircraft downtime minimization, current robot management systems often lack the scalability, flexibility, and robustness required for complex, real-world deployments involving humanoid robots beyond material handling operational scenarios.
Current research emphasizes the integration of advanced sensing capabilities, such as computer vision and tactile feedback, into humanoid robots to enable them to perform intricate maintenance tasks, such as component inspection and repair, with increasing autonomy and precision to support a shift in robot fleet management towards decentralized control architectures that allow humanoid robots to adapt to changing task priorities and collaborate more effectively with human personnel.
This project seeks to develop a humanoid fleet management system that provides a centralized platform for monitoring, controlling, and coordinating the activities of multiple robots across a variety of manufacturing and sustainment operations.
The system should enable autonomous task allocation based on robot capabilities and availability, optimize resource utilization, allow real-time monitoring and control, facilitate seamless communication between robots and human operators, and adapt to dynamic changes in the operational environment.
The system should be scalable to fleets of varying sizes and adaptable to different humanoids, other robot platforms, and operational scenarios. This is a Direct-to-Phase II initiative. Companies must demonstrate, from the outset, (1) a prototype system capable of basic fleet monitoring for mobile and non-mobile platforms, task assignment, and adaptive autonomous robot control in a simulated environment.
(2) An understanding of the challenges associated with managing and coordinating humanoid robot fleets and propose innovative solutions for addressing these challenges. (3) Proven experience deploying autonomous systems performing manufacturing and sustainment activities beyond material handling. Provide a clear plan for scaling the system to larger fleets and more complex operational scenarios.
Develop a functional prototype of the humanoid fleet management system and demonstrate its performance on a physical fleet of robots including humanoid, non-humanoid mobile, and non-mobile industrial robotics platforms.
Evaluate the system's effectiveness in coordinating the robots to perform a range of collaborative tasks in a real-world environment, showcasing its ability to adapt to dynamic conditions and optimize resource utilization. Quantify the performance improvements achieved through fleet management compared to individual robot operation.
Refine the system based on experimental results, focusing on scalability, robustness, and user-friendliness. The expected TRL from Phase II is TRL 7 or 8. If Phase II is successful, Phase III will focus on transitioning the fleet management system to a commercially viable product.
This includes further development and refinement of the system, rigorous testing and validation in diverse operational environments, and integration with existing robotic platforms and control systems. Explore potential applications in various sectors, including manufacturing, logistics, and inspection.
Develop partnerships with robotics manufacturers to integrate the fleet management system into their product offerings, paving the way for widespread adoption of humanoid robot fleets across a range of industries. If you can achieve the objective above better than any other company on the market, you have a very high-likelihood of success and should apply. Who is eligible to apply?
Any company that meets the following criteria: U.S.-owned and controlled. 500 or fewer employees (including affiliates) 1) End-to-end support including, strategy, writing of the full proposal, and administrative & compliance support. 2) Proposal strategy and review.
3) Administrative & compliance support. Request to talk with a member of our team by completing the form below: Aerospace & Spacetech Robotics & Autonomous Systems Defense & Dual Use Technology Air Force Artificial Intelligence & Machine Learning https://www. bwcoconsulting.
com Safe Falling and Failing For Humanoid Robots - SBIR Topic DAF26BZ03-DV019 Nickel Molybdenum Hard Chrome Alternative - SBIR Topic DAF26BZ03-DV021
According to the current listing, eligibility includes: U. S. for-profit small business concerns under SBA size standards (fewer than 500 employees). At least 51% U. S. -owned and independently operated. Direct-to-Phase-II requires demonstrated Phase I-equivalent work. Confirm the full requirements in the official notice before applying.
The current listing shows up to $2,000,000 USD per Phase II award under the Direct-to-Phase-II SBIR pathway. Verify award ceilings, matching requirements, and allowable costs in the official notice.
Applications for Air Force SBIR DAF26BZ03-DV020 AI-Driven Humanoid Robotic Fleet Management for Aircraft Maintenance and Sustainment are due July 22, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Air Force SBIR DAF26BZ03-DV020 AI-Driven Humanoid Robotic Fleet Management for Aircraft Maintenance and Sustainment is funded by U.S. Department of the Air Force (AFWERX SBIR). 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.
Air Force SBIR topic DAF26BZ03-DV019 seeks AI-driven solutions for fall detection, impact mitigation, and autonomous recovery technology for humanoid robots in military maintenance, logistics, and hazardous operations environments. Goals include reducing damage from falls, improving robot reliability under unstructured operational conditions, enabling safe human-robot collaboration in mixed teams, and developing predictive ML models that anticipate failure modes before they occur. Applicable to aircraft maintenance, ground sustainment, and contested logistics use cases.
Air Force SBIR topic DAF26BZ03-DV020 seeks advanced AI-driven solutions for a scalable fleet management platform coordinating humanoid, mobile, and industrial robots performing aircraft maintenance and sustainment. Requirements include autonomous AI-based task allocation, real-time monitoring, human-robot collaboration workflows, dynamic scheduling, multi-modal sensor fusion for situational awareness, and operational optimization. Solutions must scale across mixed robotic fleets in active Air Force maintenance environments and contested logistics scenarios.
Air Force SBIR DAF26BZ03-DV019 Safe Falling and Failing for AI-Enabled Humanoid Robots in Maintenance and Logistics is sponsored by U.S. Department of the Air Force (AFWERX SBIR). Air Force SBIR topic DAF26BZ03-DV019 seeks AI-driven solutions for fall detection, impact mitigation, and autonomous recovery technology for humanoid robots in military maintenance, logistics, and hazardous operations environments.
DARPA Young Faculty Award is sponsored by Defense Advanced Research Projects Agency (DARPA). The DARPA Young Faculty Award program identifies and engages rising academics in early-career research positions, particularly those with minimal prior DARPA funding, to expose them to Department of Defense (DOD) needs. The Defense Sciences Office (DSO) within DARPA has open topic areas in Physical Sciences, including open quantum systems, quantum-enhanced sensing, novel qubit platforms, complex chemical systems, nuclear systems and beams, nuclear particle/photon interactions, and nonequilibrium thermodynamics.
Operation Stonegarden (OPSG) is a federal grant program administered by FEMA through the Office of the Governor's Public Safety Office that funds enhanced border security cooperation among Customs and Border Protection (CBP), U.S. Border Patrol, and state, local, tribal, and territorial law enforcement agencies. The program supports joint operations to secure land and water border routes, improve intelligence sharing, and expand 287(g) screening operations within correctional facilities. In 2025, the national priority is Supporting Border Crisis Response and Enforcement, covering training, operational coordination, and risk management. Eligible expenses include operational overtime costs, staffing support for screening activities, and training programs in immigration law, civil rights protections, and 287(g) procedures.
DoD Multidisciplinary Research Program of the University Research Initiative (MURI) is sponsored by Department of Defense (DoD) - Office of Naval Research (ONR). The Multidisciplinary Research Program of the University Research Initiative (MURI), administered by the Department of Defense Office of Naval Research, supports basic research in science and engineering at U. S.
The DSO DPA26BZ03 drop pairs a wearable closed-loop sleep system and a host-pathogen interactome predictor with a brutal Rydberg-sensor manufacturing topic and air-independent high-density batteries. All four open June 24 and close July 22, 2026. Here is what each topic is really asking for, and which small businesses are positioned to win.
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