Agata Barcis — accepted AI-conference papers

2025

Distributed Loitering Synchronization with Fixed-Wing UAVs

Ahmed AlKatheeri, Agata Barcis, Eliseo Ferrante

ICRA 2025

Distributed loitering synchronization is the process whereby a group of fixed-wing Unmanned Aerial Vehicles (UAVs) align with each other while they follow a circular path in the air. This process is essential to establish proper initial conditions for missions in the real world. We evaluate the perf

Cited by 0 Source ↗Scholar ↗

2024

A Sim-to-Real Deep Learning-Based Framework for Autonomous Nano-Drone Racing

Lorenzo Lamberti, Elia Cereda, Gabriele Abbate, Lorenzo Bellone, Victor Javier Kartsch Morinigo, Michal Barcis +4

RA-L 2024

Autonomous drone racing competitions are a proxy to improve unmanned aerial vehicles' perception, planning, and control skills. The recent emergence of autonomous nano-sized drone racing imposes new challenges, as their <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http

Cited by 14 Source ↗Scholar ↗

2024

Corrections to "a Sim-to-Real Deep Learning-Based Framework for Autonomous Nano-Drone Racing"

Lorenzo Lamberti, Elia Cereda, Gabriele Abbate, Lorenzo Bellone, Victor Javier Kartsch Morinigo, Michal Barcis +4

RA-L 2024

Presents corrections to the article “a Sim-to-Real Deep Learning-Based Framework for Autonomous Nano-Drone Racing”.

Cited by 1 Source ↗Scholar ↗