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Autonomous Triage and Evacuation in Large Scale Combat Operations

Large Scale Combat Operations (LSCO) between peer adversaries can lead to mass casualty scenarios where the demand for medical evacuation and care exceeds available resources. This call aims to develop and validate innovative Robotic and Autonomous Systems (RAS) to enhance battlefield triage and evacuation, particularly in environments affected by Chemical, Biological, Radiological, and Nuclear (CBRN) threats and high-intensity combat zones. The call seeks solutions that integrate unmanned air, ground, and sea vehicles to increase casualty evacuation capacity and improve battlefield triage automation. These solutions must support rapid, autonomous, and robotic-assisted casualty care and evacuation while ensuring protection and patient monitoring.

The proposed solutions should provide a scalable, interoperable, and modular approach to battlefield casualty care, supporting quick reconfiguration between different medical and non-medical missions. Proposals must also integrate trusted autonomy to facilitate networked and automatic CASEVAC missions, enabling manned-unmanned teaming (MUM-T) operations. Additional functionalities include incorporating wearable patient monitoring systems, miniaturized CBRN sensors, and AI-based algorithms for automated triage assessment. Ethical considerations, responsibility frameworks, and explainability of AI decisions should also be addressed.

This call supports the study and design of RAS CASEVAC systems, focusing on feasibility analysis, proof-of-concept demonstrations, and the development of mission planning tools. The expected impact includes enhanced casualty location and triage accuracy, improved protection and transport efficiency, and reduced risk exposure for medical personnel. The initiative will advance the development of AI-driven medical logistics, human-machine teaming, and autonomous battlefield evacuation technologies.

Opening: 18-02-2025
Deadline(s): 16-10-2025

Expected Outcome

- Improved battlefield triage accuracy and efficiency through autonomous decision-making.
- Enhanced casualty evacuation capacity, reducing medical response times.
- Increased survivability of wounded soldiers through early automated interventions.
- Reduction of risk exposure for combat medics and first responders.
- Improved interoperability and modularity of RAS CASEVAC platforms.
- Integration of AI-driven assessment tools for medical decision-making.
- Advancements in autonomous casualty extraction from high-threat environments.
- Enhanced protection measures for patients during transport in hostile areas.
- Development of real-time multimodal battlefield monitoring tools.
- Establishment of a roadmap for future RAS CASEVAC system development.

Scope

- Development of Robotic and Autonomous Systems (RAS) for military battlefield triage and evacuation.
- Integration of AI-driven triage systems for rapid assessment of casualties.
- Deployment of unmanned CASEVAC platforms capable of autonomous casualty transport.
- Incorporation of wearable health monitoring sensors and CBRN detection systems.
- Ensuring adaptability to adverse weather, terrain, and combat conditions.
- Development of modular, plug-and-play CASEVAC platforms with rapid reconfiguration capabilities.
- Enhancement of manned-unmanned teaming (MUM-T) operations for autonomous evacuation.
- Implementation of ethical frameworks for AI-driven triage decision-making.
- Study of casualty extraction and safe handover between different platforms.
- Development of mission planning tools integrating AI-based algorithms and real-time battlefield updates.

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