Education

PhD in Robot Learning.

ETH and University of Zurich, 2021. Summa cum laude. I was funded by a series of Intel Research Grants and NCCR robotics. I won the Georges Giralt Award for my work, the most prestigious recognition for a PhD dissertation in robotics in Europe.

Awards

  • Outstanding Reviewer Award Robotics and Automation Letters (RA-L), 2022.
  • Best Paper Award Honorable Mention IEEE Transactions on Robotics (T-RO), 2020.
  • Best Paper Award Finalist Conference on Robotics and Intelligent Machines (IRIM-3D), 2020.
  • Best Paper Award Finalist Robotics: Science and Systems (RSS), 2020.
  • Best System Paper Award Conference on Robotic Learning (CoRL), 2018.
  • ETH-Medal for Outstanding Master Thesis, 2017.

Selected Publications

The following are my favourite publications. A complete list of publications can be found on my Google Scholar profile and my Publications page.

Drone Acrobatics

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!

Uncertainty Estimation

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

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!

Nano-Dronet

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!

News

  • July, 2022. I gave a keynote on agile flight at a robotics seminar at MIT!
  • June, 2022. I won the Georges Giralt PhD Award!
  • June, 2022. One paper accepted to Science Robotics!
  • May, 2022. I gave three keynotes at different workshops at ICRA on agile flight and the value of competitions for robotics research!
  • May, 2022. I organized the DodgeDrone Competition at ICRA 2022!
  • Mar, 2022. I gave a talk about the key ingredients for autonomous flight at the AiR Seminar in Toronto!
  • Mar, 2022. One paper accepted at Plus-One!
  • Feb, 2022. I gave a talk about the affinities between computer vision and robotics at an ELLIS Seminar in Turin!
  • Jan, 2022. One paper accepted at RAL-ICRA 2022! Looking forward to meet colleagues in Philadephia in may!
  • Nov, 2021. I've started my PostDoc at UC Berkeley!
  • Oct, 2021. Our latest paper Learning High-Speed Flight in the Wild was published in Science Robotics! Our work was featured in IEEE Spectrum and Forbes, amongs others!
  • May, 2021. I successfuly defended my PhD thesis Learning Agile Robot Navigation with summa cum laude! Check out the video recording on YouTube! I will continue as a PostDoc at the same lab!
  • Apr, 2021. My paper Deep Drone Racing: From Simulation to Reality with Domain Randomization won the Best Paper Award Honorable Mention for the journal Transactions on Robotics (T-RO)!
  • Mar, 2021. I am co-organizing the workshop on Perception and Action in Dynamic Environments and the associated DodgeDrone Challenge . Feel free to join if you are interested in computer vision, machine learning, or control in complex environments!
  • Dec, 2020. My paper Agile Autonomy: High-Speed Flight with On-Board Sensing and Computing was nominated for the Best Paper Award at IRIM-3D 2020!
  • Oct, 2020. One paper accepted at the Conference on Robotic Learning (CoRL) 2020!
  • Sept, 2020. One paper accepted at the Conference Neural Information Processing Systems (NeurIPS) 2020!
  • July, 2020. My paper Deep Drone Acrobatics was nominated for the Best Paper Award at RSS 2020!
  • July, 2020. One paper accepted at European Conference on Computer Vision (ECCV), 2020.
  • June, 2020. One paper accepted at the IEEE Robotics and Automation Letters (RA-L) and IROS, 2020.
  • June, 2020. I gave a keynote talk together with Prof. Davide Scaramuzza about Uncertainty Estimation in Deep Learning and Drone Acrobatics at the ICRA 2020 Workshop Perception, Action, and Learning. A recording of the talk is available at this link.
  • May, 2020. I gave a talk about Learning Agile Flight at the UZH Deep Learning Symposium. A recording of the talk is available at this link.
  • May, 2020. One paper accepted at the Robotics, Science and Systems (RSS) Conference, 2020.
  • April, 2020. My paper Learning Depth with Very Sparse Supervision was presented as a Spotlight at the ICLR 2020 Workshop Bridging AI and Cognitive Science (BAICS).
  • Jan., 2020. One paper accepted for publication at the Robotics and Automation Letters (RA-L) and Internation Conference for Robotics and Automation (ICRA), 2020.
  • Nov., 2019. I gave a talk about autonomous drone navigation and event cameras at the Zurich Machine Learning Meetup. A recording of the talk is available at this link.
  • July, 2019. One paper accepted at the IEEE Transactions on Robotics Journal (TR-O), 2019.
  • July, 2019. One paper accepted at the IEEE International Conference on Computer Vision (ICCV), 2019.
  • March, 2019. One paper accepted at the IEEE Internet of Things (IoT) Journal, 2019.
  • Feb., 2019. One paper accepted at the IEEE Conference on Computer Vision (CVPR), 2019.
  • Sept., 2018. One paper accepted at the Conference on Robotics Learning (CORL), 2018.
  • April, 2018. I am spending a six month exchange period at the UCLA Vision Lab lead by Prof. Stefano Soatto.
  • Feb., 2018. One paper accepted at the IEEE Conference on Computer Vision (CVPR), 2018.
  • Jan., 2018. One paper accepted at the IEEE Robotics and Automation Letters (RA-L), 2018.
  • June, 2017. I was awarded the ETH Medal for outstanding master thesis.