Project description
Emergency response through AI and drone-ground integration
In crisis situations, effective emergency operations depend on fast, reliable and intelligent coordination of drones and ground systems under highly dynamic and uncertain conditions. Supported by the Marie Skłodowska-Curie Actions programme, the EASIER project is developing an AI-powered response system that will automatically generate emergency operation plans using large language models. Additionally, the project is working on building advanced optimisation and reinforcement learning techniques that can balance conflicting objectives (timeliness, area coverage, resource allocation), including dealing with uncertainty in terms of drone energy depletion. By improving how drones and ground systems are coordinated in complex and uncertain emergencies, EASIER will ultimately help to save lives and reduce the impact of disasters.
Objective
EASIER is an ambitious interdisciplinary project that aims to address aerial-ground collaborative emergency response scheduling by integrating cutting-edge artificial intelligence with advanced optimization methods. Emergency response scenarios, such as flood reconnaissance, wildfire monitoring, or search-and-rescue, require rapid, flexible, and reliable scheduling solutions. However, current optimization methods are either too rigid, too expert-dependent, or insufficiently robust to handle the uncertainties and dynamic nature of real operations.
To address these challenges, EASIER builds on three methodological pillars: (i) a large language model-assisted multi-agent scheduling framework that lowers the expertise barrier by translating natural-language mission requirements into structured problem definitions and solver configurations; (ii) a multi-objective optimization solver that combines knowledge-driven heuristics and data-driven transfer learning to efficiently balance competing performance criteria; and (iii) a robust optimization solver hybridized with reinforcement learning to effectively manage uncertainties in UAV endurance. The two solvers and existing exact solvers will be integrated into the scheduling framework and validated on a high-fidelity simulation platform, ensuring both technical feasibility and operational relevance.
The originality of EASIER lies in its seamless combination of generative AI, optimization theory, and reinforcement learning in the context of aerial-ground collaboration, making it the first systematic attempt to bridge human natural-language intent with operational scheduling algorithms. The project will not only advance scientific knowledge but also deliver practical open-access tools that enhance the flexibility, robustness, and accessibility of emergency response services across Europe, in line with the EU Drone Strategy 2.0.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- engineering and technology electrical engineering, electronic engineering, information engineering electronic engineering robotics autonomous robots drones
- natural sciences computer and information sciences artificial intelligence heuristic programming
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
E1 4NS LONDON
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.