Learning Agile Flight in the Wild
Antonio Loquercio, Elia Kaufmann, Rene Ranftl, Matthias Mueller, Vladlen Koltun, Davide Scaramuzza.
Science Robotics, 2021
Deep Drone Acrobatics
Elia Kaufmann, Antonio Loquercio, Rene Ranftl, Matthias Mueller, Vladlen Koltun, Davide Scaramuzza.
Robotics, Science, and Systems (RSS), 2020
RSS 2020 Best Paper Award Honorable Mention!
Finalist for 'Create the Future Design Contest' (4 out of 700 submissions!)
This work was covered by media worldwide!
A General Framework for Uncertainty Estimation in Deep Learning
Antonio Loquercio, Mattia Segu,
Davide Scaramuzza.
IEEE Robotics and Automation Letters
(RA-L), 2020
Deep Drone Racing: From Simulation to Reality with Domain Randomization
Antonio Loquercio, Elia Kaufmann, Rene Ranftl, Alexey Dosovitskiy, Vladlen Koltun, Davide Scaramuzza.
IEEE Transactions on Robotics (T-RO), 2020
Best Paper Award Honorable Mention for the Transactions on Robotics journal (T-RO), 2020!
The conference version of this work won the Best System Paper Award at the Conference on Robotic Learning (CoRL), 2018!
A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones
Daniele Palossi, Antonio Loquercio, Francesco Conti, Eric Flamand, Davide Scaramuzza, Luca Benini.
IEEE Internet of Things Journal, 2019
DroNet: Learning to Fly By Driving
Antonio Loquercio, Ana I. Maqueda, Carlos R. del-Blanco, and Davide Scaramuzza
IEEE Robotics and Automation Letters
(RA-L), 2018
This work was featured by Media Worldwide!