Angelos Antonopoulos

About

Angelos Antonopoulos is a leading researcher in autonomous systems and uncrewed aerial vehicle (UAV) navigation, with a particular focus on robust localization in challenging environments. His most cited work, "A ROS Multi-Tier UAV Localization Module Based on GNSS, Inertial and Visual-Depth Data" (2022, 16 citations), addresses a critical gap in UAV operations: reliable positioning when Global Navigation Satellite Systems (GNSS) are unavailable. Antonopoulos developed a multi-sensor fusion framework that integrates inertial measurement units with visual and depth data, enabling drones to navigate accurately in GNSS-denied settings such as indoor spaces, urban canyons, or disaster zones. This contribution is vital for expanding UAV applications in search-and-rescue, infrastructure inspection, and autonomous logistics. By leveraging the Robot Operating System (ROS), his work provides a modular, scalable solution that has influenced subsequent research in resilient drone autonomy. Antonopoulos’s research continues to push the boundaries of sensor integration and real-time localization, making him a notable figure in the field of autonomous robotics and aerial systems.

Research Focus

Key Achievements

Top Papers

1. 1
   A ROS Multi-Tier UAV Localization Module Based on GNSS, Inertial and Visual-Depth Data

   16 citations · 2022

Key Collaborators

Contact & Links