Funded by the European Union under the Horizon Europe programme.
Grant Agreement No. 101299316, 2026–2030.
Topic(s): HORIZON-MSCA-2025-SE-01-01.
About
Robots hold great potential to support humans in extreme environments—such as post-disaster zones—where conditions are hazardous, unpredictable, and often lack reliable connectivity. Their capacity to operate in dangerous or inaccessible areas makes them crucial for search and rescue, damage assessment, and emergency response. Yet, conventional robotic systems often struggle in such contexts due to limited adaptability, fragile autonomy, and insufficient coordination. Challenges like degraded sensor inputs, dynamic unstructured terrains, GPS-denied environments, and constrained communications further hinder their effectiveness. While embodied AI has significantly enhanced the perception and action capabilities of individual robots, its focus has largely remained on single-agent systems. Achieving efficient multi-robot collaboration under uncertain, real-time, and bandwidth-limited conditions remains a major research frontier. The DIRECT project tackles these challenges by developing an innovative distributed machine learning framework that enables a fleet of robots to collaboratively perceive, reason, plan, and act in extreme environments.
DIRECT will establish a new frontier in collaborative robotics by deploying resilient, intelligent multi-robot systems to support humanitarian missions in disaster-stricken and resource-constrained environments. By harnessing distributed intelligence and seamless coordination among autonomous agents, DIRECT equips emergency services with powerful tools to accelerate search-and-rescue operations, safeguard civilian lives, and optimise scarce resources under extreme conditions. These capabilities will not only transform how responders operate in high-risk scenarios but also reinforce Europe's strategic ambition to lead in next-generation robotics, AI, and disaster resilience. In doing so, DIRECT will enhance the EU's preparedness for complex crises worldwide, strengthen its humanitarian leadership, and open inclusive opportunities for researchers and innovators—including those affected by ongoing conflicts—to contribute to Europe's technological and societal resilience.
Develop a four-stage pipeline (perception, reasoning, planning and action) that enables distributed task execution across a robot swarm in disaster zones.
Design a resilient federated learning model optimized for limited connectivity and hardware constraints.
Develop a 6G-powered integrated sensing–computing–communication infrastructure that supports collaborative perception, reasoning and co-planning.
Implement human-in-the-loop collaborative decision-making for remote support of multi-robotic systems.
Validate the DIRECT framework through simulation, benchmark model and dataset development.
News & Events
The consortium holds its kick-off meeting at the University of Warwick, setting the research agenda for four years of resilient collaborative robotics.
Details of the project's first open training workshop will be announced here.
Documents
Deliverables, publications, datasets and software produced by the DIRECT consortium will be made available here as the project progresses.
Formal project deliverables submitted to the European Commission throughout the project lifetime.
To be published.
Peer-reviewed papers, conference proceedings and preprints authored by the DIRECT consortium.
To be published.
Benchmark datasets collected and released to support multi-robot perception and planning research.
To be published.
Open-source code, simulation environments and toolkits developed as part of the DIRECT framework.
To be published.
Consortium
DIRECT brings together 19 partners across universities, research institutes and industry, with complementary expertise in robotics, distributed AI and extreme-environment operations.
Coordinator
Connected and Collaborative Robotics Lab (CCR Lab) — integrating AI with advanced communication and networking for seamless robot-to-robot and human-to-robot collaboration.
Contact
Dr. Zhenhui Yuan
Assistant Professor
Connected and Collaborative Robotics Lab (CCR Lab)
University of Warwick, United Kingdom
zhenhui.yuan@warwick.ac.uk
Funded by the European Union under the Horizon Europe programme.
Grant Agreement No. 101299316, 2026–2030.
Topic(s): HORIZON-MSCA-2025-SE-01-01.