EventsDrones 2026: Mapping the Knowledge
Published
This submission belongs to the session S6. Drones in Security and Defense of the event Drones 2026: Mapping the Knowledge
Published date
12 Nov, 2026
Contribution&Funding
Conceptualization,
[Serge Chaumette]
Methodology,
[Serge Chaumette]
Software,
[Serge Chaumette]
Validation,
[Serge Chaumette]
Formal analysis,
[Serge Chaumette]
Investigation,
[Serge Chaumette]
Writing - original draft,
[Serge Chaumette]
Writing - review,
[editing] ; [Serge Chaumette]
Supervision,
[Serge Chaumette]
Project administration,
[Serge Chaumette]
Funding acquisition,
[Serge Chaumette]
Funding: This €6.5 million initiative (ANR-23-DMRO-0009) is supported by the French State and coordinated by the National Research Agency (ANR) under the Défis Transfert Robotique challenge, part of France 2030
Citation
Serge Chaumette, Drones and Drone Swarms: Key Players in Securing Critical Infrastructures, in Proceedings of Drones 2026: Mapping the Knowledge, Barcelona, 11 November–13 November 2026, MDPI: Basel, Switzerland
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Drones and Drone Swarms: Key Players in Securing Critical Infrastructures

1. Computer Science Laboratory (LaBRI), Univ. Bordeaux, CNRS, Bordeaux INP, LaBRI, UMR 5800, Talence, F-33405, France
Abstract

The security of airports, nuclear plants, oil and gas storage facilities, etc. is gaining importance due to geopolitical context. The Padrone.AI project aims to develop a platform helping Critical Infrastructure Owners and Operators manage and secure their assets. Its current implementation focuses on airports. It brings together 17 partners, including four research laboratories and 13 companies. This €6.5 million initiative (ANR-23-DMRO-0009) is supported by the French State and coordinated by the National Research Agency (ANR) under the Défis Transfert Robotique challenge, part of France 2030.

Drones and drone swarms are key players in this layered platform. The first level consists of sensors (LiDAR, vibration sensors, cameras, etc.). When an alert is raised, edge AI determines whether it can be dismissed as a false positive or requires further investigation. If not, an AI-based hypervisor determines the appropriate action. The first step is deploying a ground robot to investigate the alert. The robot assesses whether further investigation is required. If so, the hypervisor can deploy a drone or swarm to gather additional information. If the alert is not dismissed by embedded AI, it is reported to a human, who makes the final decision.

Drones and AI, as key components, raise several challenges. Flying drones near airports is highly regulated worldwide, and authorities require guarantees regarding operational safety and reliability. Although obtaining authorization can be challenging, it is possible for specific operations. In our project, AI introduces an additional level of uncertainty. We therefore focus on two main directions: improving the explainability of AI-based decisions and developing security mechanisms, such as geofencing, to ensure safe and fully controlled operations during missions.

The project started in January 2025. After these 20 months of theoretical work and unitary experimentations, we are now in the process of combining its components around a central backbone.

Keywords
drones
swarms of drones
critical infrastructures
security
artificial intelligence
regulation
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