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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.
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Air Force SBIR: Safe Falling and Recovery Systems for Humanoid Robots — BW&CO Safe Falling and Failing For Humanoid Robots - SBIR Topic DAF26BZ03-DV019 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.
Integrated System Mitigates Fall Damage to Humanoid Robots and Ensures Operational Recovery with Minimized Performance Degradation 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 the sector of humanoid robotics, there has been significant progress in technological maturity, opening their applicability to Air Force operations, such as maintenance activities, hazardous environment exploration, and assistance with physically demanding tasks.
Humanoid robots have the capability to access areas and support operations traditionally done by human personnel, focusing on tasks that have posed significant challenges for their repetitive or strenuous nature.
Noting that these tasks are often adjacent to those which are more suited to the adaptability of human personnel, promoting safe and effective human-robot collaboration environments allows for improved performance through careful consideration of workspace design and task allocation to minimize potential hazards.
Establishing effective coordination of humanoid robots within environments where they are to perform near human personnel on complex tasks remains a hurdle to developing control strategies that ensure improvements in personnel safety and overall productivity. Of significant note is the inherent instability and susceptibility to falling of humanoid robots, which pose a significant challenge to their widespread deployment.
Despite the fact that falls can lead to costly repairs, operational downtime, and even complete robot failure, current fall mitigation strategies are often limited in their effectiveness and can significantly hinder robot agility and performance.
This project seeks to develop a comprehensive safe falling system that allows humanoid robots to autonomously detect imminent falls, react in real-time to minimize impact forces, and recover gracefully. This system should include software algorithms for fall detection and recovery strategies, and/or hardware considerations for mitigating damage and ensuring safe landing.
The system should be robust enough to handle falls from various heights and orientations, while remaining lightweight and minimally intrusive to the robot's design and performance during regular operation. Additionally, the system should be adaptable for different humanoid applications and specifications. This is a Direct-to-Phase II initiative.
Companies must demonstrate, from the outset, a prototype system capable of detecting falls in a simulated environment. This includes presenting algorithms for fall detection and preliminary strategies for impact mitigation. Demonstrate an understanding of the integration challenges and potential solutions for incorporating the system onto a physical humanoid robot platform.
Provide a clear plan for testing and validation of the proposed system. Develop a functional prototype integrated onto an existing humanoid robot platform. Demonstrate the system's effectiveness in real-world fall scenarios, showcasing its ability to detect falls, activate mitigation strategies, and minimize damage.
Quantify the system's performance in terms of impact reduction, recovery time, and overall robustness. Refine the system based on testing results, optimizing for performance, reliability, and adaptability to different humanoid platforms. The expected TRL from Phase II is TRL 7 or 8.
If Phase II is successful, Phase III will focus on transitioning the technology to a production-ready state. This includes further refinement of the system, rigorous testing and validation in diverse operational environments, and development of user-friendly interfaces for system configuration and monitoring. Explore potential applications in various sectors.
Integrate the safe falling system into commercially available humanoid robots. This technology has the potential to significantly improve the robustness and reliability of humanoid robots, accelerating their adoption across a wide range of applications. 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 Development of Directed Energy Systems for Space-Based Applications - SBIR Topic DAF26BX03-DV505 Humanoid Robotic Fleet Management - SBIR Topic DAF26BZ03-DV020
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 prior 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-DV019 Safe Falling and Failing for AI-Enabled Humanoid Robots in Maintenance and Logistics are due July 22, 2026. Build your timeline backwards from this date to cover registrations, approvals, and final submission checks.
Air Force SBIR DAF26BZ03-DV019 Safe Falling and Failing for AI-Enabled Humanoid Robots in Maintenance and Logistics 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.
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