International Conference on Robotics and Automation (ICRA) 2019 Accepted Full-Day Workshop
Dr. Aleksandra Faust, Senior Research Scientist, Google Brain, email@example.com, http://www.afaust.info
Dr. Vijay Janapa Reddi, Associate Professor in Electrical Engineering, Harvard University, firstname.lastname@example.org, https://www.seas.harvard.edu/directory/vjanapa-reddi
Dr. Angela Schoellig, Assistant Professor, University of Toronto, email@example.com, http://www.dynsyslab.org/prof-angela-schoellig/
Dr. Sarah Tang, University of Pennsylvania/Nuro, Inc., firstname.lastname@example.org, http://www.sarahtang.net
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:
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.
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 strongly prefer work featuring experimental validation (including initial preliminary results) but will also consider simulation-only papers that convincingly address why the utilized simulator is a compelling representation of real-world conditions. 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.
Paper submission deadline: 24-Mar-2019
Author notification: 25-Apr-2019
Workshop: 23 or 24-May-2019