This project is maintained by uav-learning-icra

Algorithms and Architectures for Learning in-the-Loop Systems in Autonomous Flight

International Conference on Robotics and Automation (ICRA) 2019 Accepted Full-Day Workshop


In past years, model-based techniques have successfully endowed aerial robots with impressive capabilities like high-speed navigation through unknown environments. However, task specifications, like goal positions, are often still hand-engineered.

To achieve true autonomy in applications such as disaster response and environmental-monitoring, unmanned aerial vehicles (UAVs) must additionally exhibit semantic understanding of tasks and environments, adaptation to unexpected changes, and robustness to unmodeled disturbances. Machine learning and deep learning have emerged as promising tools for higher-level autonomy, but are more difficult to analyze and implement in real-time.

Furthermore, maintaining high thrust-to-weight ratios for agility directly contradicts the need to carry sensor and computation resources, making hardware and software architecture equally crucial decisions.

This workshop aims to bring together researchers in the complementary fields of aerial robotics, learning, and systems to discuss the following themes:

Workshop Objectives

The objectives of this workshop are to:

We will host invited speakers that give a broad view of the state-of-the-art. This will include academic faculty as well as industry speakers on the commercial side and research side of UAV innovation.

Call for Papers

We are soliciting submissions of 4-page short papers (not including references) with up to a 2-minute accompanying video. Possible topics of interest include, but are not limited to:

We welcome work with experimental validation (including initial preliminary results) or addressing challenges associated with real-world implementation. We also welcome simulation-only papers that convincingly address why the utilized simulator is a compelling representation of real-world conditions and papers with validation on other robotics platforms that could be applied to UAVs. We especially encourage papers that share valuable “failure analyses” or “lessons learned” that would benefit the community. We welcome work at all stages of research, including work-in-progress and recently accepted or published results.

Important Dates

Paper submission deadline: 24-Mar-2019, 11:59PM Anywhere on Earth (AOE) EXTENDED: 7-Apr-2019, 11:59PM Anywhere on Earth (AOE)

Author notification: 25-Apr-2019 29-Apr-2019

Workshop: 24-May-2019

Submission link: https://easychair.org/my/conference.cgi?conf=lsaf19

Paper submission instructions: IEEE templates for LaTeX and MS-Word are available from the IEEE PaperPlaza website. Final submissions should be in pdf format.

Video submission instructions: Please include a link to any videos in the text of the submission. Videos can be uploaded to Youtube (as an unlisted video), Dropbox, Google Drive, or a personal webpage. Please make sure to verify video permission settings.

Any additional questions can be directed to: lsaf19@easychair.org


Dr. Aleksandra Faust, Senior Research Scientist, Google Brain, faust@google.com, http://www.afaust.info

Dr. Vijay Janapa Reddi, Associate Professor in Electrical Engineering, Harvard University, vjreddi@seas.harvard.edu, https://www.seas.harvard.edu/directory/vjanapa-reddi

Dr. Angela Schoellig, Assistant Professor, University of Toronto, schoellig@utias.utoronto.ca, http://www.dynsyslab.org/prof-angela-schoellig/

Dr. Sarah Tang, University of Pennsylvania/Nuro, Inc., sytang@alumni.seas.upenn.edu, http://www.sarahtang.net