Publications

My research focuses on robotics, computer vision, neuroscience and reinforcement learning. My goal is to build an autonomous drone that learns to fly fast by interacting with the environment. Here you can find materials relevant to my published research and research in progress.

A complete list of publications can also be found on my Google Scholar profile.

PhD Thesis

A. Loquercio.
Learning Agile Robot Navigation
University of Zurich, 2021.

Journals

P. Foehn, E. Kaufmann, A. Romero, R. Penicka, S. Sun, L. Bauersfeld, T. Laengle, G. Cioffi, Y. Song, A. Loquercio, D. Scaramuzza
Agilicious: Open-source and open-hardware agile quadrotor for vision-based flight
Science Robotics, 2022.

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Code

C. Pfeiffer, S. Wengler, A. Loquercio, D. Scaramuzza
Visual attention prediction improves performance of autonomous drone racing agents
PLOS ONE Vol. 17, Issue 3, 2022

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Dataset

A. Loquercio, A. Saviolo, D. Scaramuzza
AutoTune: Controller Tuning for High-Speed Flight
IEEE Robotics and Automation Letters (RA-L) and ICRA, 2022.

A. Loquercio, E. Kaufmann, R. Ranftl, M. Mueller, V. Koltun, D. Scaramuzza.
Learning High-Speed Flight in the Wild
Science Robotics, 2021.

A. Loquercio, A. Dosovitskiy, D. Scaramuzza
Learning Depth with Very Sparse Supervision
IEEE Robotics and Automation Letters (RA-L) and IROS, 2020.
Also presented as a Spotlight Presentation at the Workshop Bridging AI and Cognitive Science (BAICS), ICLR 2020.

A. Loquercio, M. Segu, D. Scaramuzza
A General Framework for Uncertainty Estimation in Deep Learning
IEEE Robotics and Automation Letters (RA-L) and ICRA, 2020.

A. Loquercio, E. Kaufmann, R. Ranftl, A. Dosovitskiy, V. Koltun, D. Scaramuzza.
Deep Drone Racing: From Simulation to Reality with Domain Randomization
IEEE Transactions on Robotics (T-RO), 2020.
T-RO Best Paper Award Honorable Mention!

D. Palossi, A. Loquercio, F. Conti, E. Flamand, D. Scaramuzza, L. Benini.
A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones
IEEE Internet of Things (IoT), 2019.

A. Loquercio, A. Maqueda, C. del-Blanco, and D. Scaramuzza
DroNet: Learning to Fly by Driving
IEEE Robotics and Automation Letters (RA-L) and ICRA, 2018.

Conferences

Equal Contribution is indicated with *

A. Loquercio and D. Scaramuzza
Agile Autonomy: High-Speed Flight with On-Board Sensing and Computing
Conference on Robotics and Intelligent Machines (I-RIM3D), 2020.
Best Paper Award Finalist!

F. Milano, A. Loquercio, A. Rosinol, D. Scaramuzza, L. Carlone
Primal-Dual Mesh Convolutional Neural Networks
Conference on Neural Information Processing Systems (NeurIPS), 2020.

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Code

Y. Song, S. Naji, E. Kaufmann, A. Loquercio, D. Scaramuzza
Flightmare: A Flexible Quadrotor Simulator
Conference on Robotic Learning (CoRL), 2020.

N. Messikommer, D. Gehrig, A. Loquercio, D. Scaramuzza
Event-based Asynchronous Sparse Convolutional Networks
European Conference on Computer Vision (ECCV), 2020.

E. Kaufmann*, A. Loquercio*, R. Ranftl, M. Mueller, V. Koltun, D. Scaramuzza.
Deep Drone Acrobatics
Robotics, Science, and Systems (RSS), 2020
Best Paper Award Finalist!

Blog Post

D. Gehrig, A. Loquercio, K.G. Derpanis, D. Scaramuzza
End-to-End Learning of Representations for Asynchronous Event-Based Data
IEEE International Conference on Computer Vision (ICCV), 2019

Y. Yang*, A. Loquercio*, D. Scaramuzza, S. Soatto
Unsupervised Moving Object Detection via Contextual Information Separation
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.

E. Kaufmann*, A. Loquercio*, R. Ranftl, A. Dosovitskiy, V. Koltun, D. Scaramuzza.
Deep Drone Racing: Learning Agile Flight in Dynamic Environments
Conference on Robotic Learning (CoRL), 2018
Best Systems Paper Award!

A. Maqueda, A. Loquercio, G. Gallego, N. Garcia, D. Scaramuzza
Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars
IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.

Y. Ye, T. Cieslewski, A. Loquercio, D. Scaramuzza
Place Recognition in Semi-Dense Maps: Geometric and Learning-Based Approaches
British Machine Vision Conference (BMVC), 2017.

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Poster

A. Loquercio, M. Dymczyk, B. Zeisl, S. Lynen, I. Gilitschenski, R. Siegwart
Efficient Descriptor Learning for Large Scale Localization
IEEE International Conference on Robotics and Automation (ICRA), 2017.

Workshops and Pre-Prints.

A. Loquercio, D. Scaramuzza
Learning to Control Drones in Natural Environments: A Survey
Spotlight Presentation at the Workshop on Perception, Inference, and Learning, ICRA 2018.