SBIR: ALIAS Missionized Autonomy for Emergency Services is a grant from DARPA under the SBIR XL program that funds development and demonstration of missionized autonomy for emergency services, with an initial focus on autonomous wildfire response using Manned-Unmanned Teaming (MUM-T) and integrated sensing technologies.

The topic leverages DARPA's Aircrew Labor In-Cockpit Automation System (ALIAS) air vehicle autonomy program using Sikorsky helicopter platforms. The effort addresses Human-Machine Interfaces, Integrated Sensing and Cyber, and Trusted AI and Autonomy as critical technology areas. Technology developed under this topic is subject to ITAR and EAR export control restrictions.

Eligible applicants are U.S. small businesses; foreign nationals involved in the work must be disclosed.

SBIR: ALIAS Missionized Autonomy for Emergency Services - SBIR XL | DARPA Department of War organization.

SBIR: ALIAS Missionized Autonomy For Emergency Services - SBIR XL SBIR: ALIAS Missionized Autonomy for Emergency Services - SBIR XL OUSD (R&E) critical technology area(s) : Human-Machine Interfaces, Integrated Sensing and Cyber, Trusted AI and Autonomy 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 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.

Objective: This topic focuses on development and demonstration of missionized autonomy for emergency services, initially focusing on autonomous wildfire response using autonomous Manned-Unmanned Teaming (MUM-T) and integrated sensing technologies.

These capabilities will leverage the DARPA Aircrew Labor In-Cockpit Automation System (ALIAS) air vehicle autonomy program, using Sikorsky’s MATRIX autonomy system on S-76 and UH-60 helicopters combined with third-party autonomy applications to execute emergency services and wildland firefighting tasks. A key focus will be on the development of autonomy applications that enhance the capabilities of these systems.

Description: This SBIR XL topic seeks proposals for developing novel autonomy applications that enhance the capabilities of the UH-60 as an autonomous aerial platform for emergency services, with a specific initial focus in wildfire suppression.

These applications will be developed utilizing DARPA ALIAS and the Sikorsky MATRIX Government Purpose Rights Software Development Kit to plug into the ALIAS autonomy stack to provide real-time decision-making, integrated sensing for situational awareness, and advanced communication technologies for coordination with ground and air units.

The ALIAS-Texas initiative will assess the ability of autonomous/semi-autonomous aircraft to support wildland firefighting operations through simulated and live test environments, covering tasks such as water or retardant drops, cargo sling loads, medical evacuations, reconnaissance, and crew shuttles.

A significant component of this project will be the development and integration of autonomy applications that enable these aircraft to perform complex tasks with minimal human intervention. The increasing frequency and intensity of wildfires necessitate advanced technologies for rapid response and suppression. Autonomous systems can significantly reduce response times and enhance the effectiveness of firefighting efforts.

The ALIAS-Texas initiative aims to develop and integrate a suite of third-party autonomy applications that work with the MATRIX system to deliver enhanced optionally piloted vehicle (OPV) capabilities optimized for sustained concurrent/collaborative multi-vehicle wildland firefighting operations, with additional capabilities pertaining to emergency services.

The focus on autonomy app development will enable these systems to perform complex tasks with minimal human intervention, improving their effectiveness and reliability in critical missions.

This initiative will leverage the existing network between the ALIAS air vehicle autonomy program, and Sikorsky’s MATRIX autonomy system, combined with newly developed third-party autonomy applications to execute emergency services and wildland firefighting tasks, including the following: Water or retardant drops using buckets or a fixed tank Autonomy applications will be developed and tested using the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) environment.

The simulation will represent terrain, wind, vegetation, and fire dynamics and will support real-time interaction and observation through conformant sensor interfaces. Initial capabilities of autonomous aircraft will be demonstrated in a controlled environment.

The initial focus will be on developing and testing autonomy applications that enable the aircraft to perform tasks such as search, localization, tracking, suppression, and assessment autonomously. Later phases of app development will expand the simulation environment to include real-world data. Field tests will be conducted with autonomous aircraft, demonstrating real-time decision-making and coordination with other emergency services.

The system will be integrated with ground control, test operations, and data acquisition environments to support concurrent control of multiple ALIAS-enabled aircraft for one or multiple operations. The development of autonomy applications will continue, with a focus on enhancing the aircraft's ability to perform complex tasks autonomously and collaboratively. Field data will be used to validate and verify autonomy app development.

This SBIR topic is open to Direct-to-Phase II (DP2) proposals only. Offerors must demonstrate existing technical maturity and feasibility of their approach through preliminary results, app prototypes, or prior autonomy work.

Proposals should clearly articulate their ability to integrate with a high-fidelity simulation environment (Generic Helicopter Model) for training, testing, and evaluation of their application, ALIAS/MATRIX autonomy and mission behaviors.

A clear transition path to Phase II should be outlined, including existing modeling and simulation environments that would support the rapid development of autonomy applications to integrate with the ALIAS/MATRIX autonomy system. Phase II efforts will focus on developing and demonstrating an operational prototype of the proposed application.

Offerors will be expected to demonstrate the performance of their autonomy plugin through operationally realistic wildfire fighting mission scenarios. In Phase II (12Month Period of Performance), proposers will be expected to: Develop a functional prototype of their mission app integrated with ALIAS/MATRIX autonomy stack utilizing ALIAS/MATRIX SDK.

Demonstrate performance in both simulation and live flight test, using S-76 and UH-60 optionally piloted helicopters Validate key app functionality through scenario-based evaluation. Capstone scenario capabilities can be included in proposal Single Aircraft: Fixed Burn Fire Suppression - Suppress a planned prescribed burn with automated drop planning and execution over a fixed area using wind and terrain aware routing.

Single Aircraft: Rooftop Personnel Recovery - Recover injured personnel from a rooftop in an urban environment using autonomous landing or hover/hoist operations under emergency conditions Multi-Aircraft: Coordinated Wildfire Suppression - Recon and suppression aircraft operate together to identify firelines, relay targets, and coordinate drops for maximum containment effect.

Single Aircraft: Cargo Sling Load - Deliver a sling-loaded supply payload from base to a forward area, autonomously managing load stability, airspeed, and LZ approach. Single Aircraft: Reconnaissance - Conduct an autonomous route or area recon using EO/IR sensors, tagging points of interest and generating a time stamped report.

Single Aircraft: Crew Shuttle Transport personnel between mission staging areas, dynamically updating routes and manifests based on C2 tasking or weather conditions. Participate in at least one government organized simulation exercise and one flight demonstration event to evaluate app performance in realistic operational conditions.

Option (12 Month Period of Performance): Additional app development for multi aircraft scenarios Expansion of app training, tactics, and procedures (TTPs) for tasking, mission monitoring, and dynamic reallocation across multiple aircraft and mission types. Refinement of airspace integration procedures to support mixed use operations in civil, military, and disaster response environments.

Validation of TTPs for intelligence, surveillance, and reconnaissance (ISR) driven multi aircraft coordination without centralized ground control. Incorporation of tactical autonomy behaviors for mission adaptation in denied, degraded, or contested environments. Development of response TTPs for distributed autonomous teams.

Collaboration with end-user organizations to tailor mission specific standard operating procedures (SOPs) and concepts of operations (CONOPS). Simulation and live testing of cross domain mission profiles, such as simultaneous fire suppression and reconnaissance, or search and rescue (SAR) with logistics delivery.

Phase III dual use applications If successful, commercial applications include rapid response to wildfires and other natural disasters. Military applications include autonomous surveillance and reconnaissance in austere environments. The system will support a broad array of engineering, testing, and training, including AI app development, aircraft-sensor-app integration, and mission-based testing.

The autonomy applications developed in this project will have broad applicability across various domains, with capability to enhance autonomous systems in both commercial and military settings. https://www. darpa.

mil/news/2025/texas-darpa-alias-testbed https://news. tamus. edu/texas-am-system-to-lead-59-8m-autonomous-helicopter-wildfire-response-initiative Autonomous, Wildfire, AI, Integrated Sensing, Emergency Services, ALIAS, MATRIX, Simulation, Firefighting, Autonomy Applications Publication: Sept.

3, 2025 DoD SBIR 2025. 4 | Release 12 HR0011SB20254XL-01 Cost Proposal Template