Programme time: 14-Oct | 15:00 | 75 min
Room: D. Luis Room (Industry 5.0)
Moderator: To be confirmed
Speakers
•    To be confirmed

Full description and objectives

UAVs are emerging as flexible tools for internal logistics, inventory management, inspection, and rapid material transport in factories and warehouses. Deep Reinforcement Learning can enable these systems to learn navigation, task allocation, and fleet coordination policies that adapt to dynamic layouts, moving obstacles, changing priorities, and uncertain operating conditions. This workshop will consist of focused presentations addressing the technologies, industrial applications, and deployment challenges associated with autonomous aerial logistics.

The objectives are to:

1. Present current research and technological developments in UAVs for factory and warehouse logistics.

2. Demonstrate how Deep Reinforcement Learning, simulation, and optimization can support navigation, scheduling, control, and decision-making.

3. Discuss autonomous UAV operations for material transport, inventory monitoring, inspection, and intralogistics.

4. Present approaches for connecting UAV fleets with digital twins, warehouse management systems, manufacturing execution systems, IoT platforms, and edge-computing infrastructure.

5. Examine safe and trustworthy Deep Reinforcement Learning, cybersecurity, explainability, operational assurance, and meaningful human oversight.

6. Discuss simulation-based training, sim-to-real transfer, testing, validation, interoperability, and standardization requirements.

7. Identify European research priorities and cooperation opportunities between research organizations, UAV providers, manufacturers, logistics operators, and industrial end users.

The session will conclude with a panel discussion and audience questions, producing a shared overview of capability gaps, adoption barriers, and future research directions for UAV-enabled logistics and learning-based autonomy.

Why you want to join?

The session will present recent developments in the use of unmanned aerial vehicles (UAVs) for autonomous logistics in factories, warehouses, and industrial production environments.

The presentations will cover UAV-based material transport, inventory monitoring, inspection, and data collection, together with the sensing, perception, communication, and artificial-intelligence technologies required for safe autonomous operation in complex industrial environments.

The workshop will explore how Artificial Intelligence, with a particular focus on Deep Reinforcement Learning, can enable autonomous, adaptive, and intelligent UAV-based logistics in dynamic factory environments. It will connect advances in aerial robotics, multi-agent AI systems, and digital twins with practical industrial requirements, addressing AI-driven path planning, autonomous task allocation, collision avoidance, fleet coordination, energy-aware decision-making, and real-time adaptation to changing operational conditions. The workshop will also examine the use of simulation and digital twins to train, test, and validate Deep Reinforcement Learning policies, as well as key challenges related to safety, cybersecurity, explainability, human oversight, and reliable deployment in real-world industrial settings.

By bringing together researchers, UAV technology providers, manufacturers, logistics operators, system integrators, and policymakers, the session will facilitate knowledge exchange and identify priorities for European research, industrial uptake, and collaboration.

Running agenda