Workshop on Self-Supervised Robot Learning

Robotics: Science and Systems
Virtual Workshop

 

 

Submission deadline EXTENDED to May 4th, 2020 AoE

Update Concerning COVID-19

The RSS 2020 SSRL organizing committee hope you are safe and well. Due to the pandemic and the uncertainty regarding travel to the US, the RSS 2020 SSRL workshop will take place VIRTUALLY on the original date of July 13th. The submission deadline has been extended to 4th May 2020. We expect to share more details regarding the online program by the end of April.


NOTE: Submission deadline EXTENDED to May 4th, 2020 AoE

Overview

Self-supervised learning is an exciting research direction that aims to learn representations from the data itself without explicit and potentially even manual supervision. One of the major benefits of self-supervised learning is the ability to scale to large amounts of unlabelled data in a lifelong learning manner and to improve performance by reducing the effect of dataset bias. Recent development in self-supervised learning has resulted in  achieving comparable or better performance than fully-supervised models. However, many of these methods are developed in domain-specific communities such as robotics, computer vision or reinforcement learning. The aim of this workshop is to bring together researchers from different communities to discuss opportunities, challenges and explore new directions.


Topics

The focus topics of our workshop include, but are not restricted to:

  • Self-supervised learning for robotics, robot vision, reinforcement learning….
  • Self-supervised domain adaptation
  • Meta-learning of self-supervised tasks
  • Large-scale self-supervised learning
  • Learning of generalizable pretext-tasks
  • Loss functions for self-supervised learning
  • Learning from auxiliary/multiple tasks
  • Multimodal and cross-modal learning

Invited Speakers

Pieter Abbeel (UC Berkeley & Covariant.AI)

Dieter Fox (University of Washington & NVIDIA)

Abhinav Gupta (CMU & Facebook AI Research)

Roberto Calandra (Facebook AI Research)

Chelsea Finn (Stanford University)

Pierre Sermanet (Google Brain)

Andy Zeng (Google Brain)


Call for Contributions

We encourage participants to submit their research in the form of a single PDF. Submissions may be up to 4 pages in length, including figures, excluding references and any supplementary material. Please use the RSS conference template. Accepted papers will be presented in a poster session and selected awards papers as spotlight talks. All submitted contributions will go through a single blind review process. The contributed papers will be made available on the workshop’s website and selected papers will be invited for a special issue of a major robotics journal.

Submission Website: https://easychair.org/conferences/?conf=ssrl20

LaTeX Template: https://roboticsconference.org/docs/paper-template-latex.tar.gz

In order to make acceptance decisions early, we request interested researchers to submit a single page extended abstract by 19th April as an expression of interest. The authors would then have time 2nd July to include new results and submit the full 4 page paper. We also welcome submissions that have already been accepted to RSS or other major conferences and journal papers that have not been discussed in a conference.


Important Dates

May 4th, 2020 (AOE) One page submission deadline (Old deadline April 19th)
May 20th, 2020 Notification of acceptance (Old date April 24th)
July 2nd, 2020 (AOE) Full paper submission
July 13th, 2020 (Virtual) Workshop

Tentative Schedule

Time
Talks
12:00-12:10 Welcome and Introductory Remarks (Organizers)
12:10-12:30 Invited Talk 1
12:30-12:50 Invited Talk 2
12:50-13:10 Invited Talk 3
13:10-13:30 Q&A + Panel Discussion 1
13:30-13:50 Contributed Papers Discussion 1
13:50-14:10 Invited Talk 4
14:10-14:30 Invited Talk 5
14:30-14:50 Invited Talk 6
14:50-15:10 Invited Talk 7
15:10-15:30 Q&A + Panel Discussion 2
15:30-15:50 Contributed Papers Discussion 2
15:50-16:00 Concluding Remarks

        
This event is organized in cooperation with ELLIS@Freiburg.