The 2nd Annual Conference on Robot Learning (CoRL 2018) is soliciting contribution at the intersection of robotics and machine learning. CoRL aims at being a selective, top-tier venue for robot learning research, covering a broad range of topics spanning robotics and ML, including both theory and practice:
We invite papers offering new advances on any of the following topics:
  • - Imitation learning, bayesian/probabilistic learning, neural networks
  • - (Inverse) reinforcement learning, model-free learning, etc.
  • - Machine learning and control
  • - Bio-inspired learning and control
  • - State estimation, mapping, and computer vision
  • - Multimodal perception and sensor fusion
  • - Learning-based human robot interaction, natural language instruction processing
  • - Applications in manipulation, mobility, driving, flight, and other areas of robotics
Accepted papers will published via the JMLR Workshop & Conference Proceedings series and will be presented either as posters or oral presentations in the plenary session. CoRL is a single track venue!

Selected papers will be invited for expedited review as regular submissions to the IEEE Transactions on Robotics or Journal of Machine Learning Research.
All papers go to the archival track. There is not the possibility to submit for non-archival track this year.

Authors are strongly encouraged to submit their code as supplementary material to the paper. Availability of code will be viewed as a plus. Your code should be uploaded on the CMT system at the same time as you submit your paper and other supplementary material (videos, proofs, etc).


Paper submission deadline:       June 15, 2018
5pm pacific time
Paper acceptance notifications: September 1, 2018
Camera ready papers due:        September 30, 2018
Papers may be submitted through CMT, via the link at the top of this page. Submissions are due June 15, 2018 at 5:00 pm PT. All submissions should comply to the format and length indicated below.  CoRL is double-blind, which means all papers must be anonymized.

Submissions will consist of papers up to eight pages in length (plus up to two additional pages of references). Authors will have the option to submit a supplementary file containing further details, which the reviewers may decide to consult, as well as a supplementary video. All supplementary materials will be submitted through CMT as a single zip file.  Submitted papers will be reviewed by three reviewers. Accepted papers will appear in the JMLR Workshop & Conference Proceedings as officially published CoRL papers. All accepted papers will be provided with a poster presentation slot, and about 20-30 papers will be presented as oral presentations in the main conference. While it is difficult to judge how many papers will be submitted or accepted, since this is the second year for CoRL, we expect a large fraction of accepted papers to receive oral presentation slots.
Submission Policy

We will not accept papers that are identical or substantially similar to papers that have previously been published or accepted for publication in an archival venue, nor papers submitted in parallel to other conferences. Archival venues include conferences and journals with formally published proceedings, but do not include non-archival workshops. Submission is permitted for papers that have previously appeared only as a technical report.

Reviewing Criteria

Submissions will be evaluated based significant novel results. Results may be either theoretical or empirical. Results will be judged on the degree to which they have been objectively established and/or their potential for scientific and technological impact, as well as their relevance to robotic learning. We take a broad view of robotic learning. Papers with both experimental and theoretical results relevant to robotic learning are welcome. Our intent is to make CoRL into a selective top-tier conference on robotic learning.

Manuscript Template
Accepted papers will be published in PMLR. The manuscript template to use is available here.
Note: The .sty file of the template has been corrected. Please download the new template if you encountered a compilation error.

Papers selected for expedited review as IEEE Transactions on Robotics or Journal of Machine Learning Research will need reformatting. Information will be sent to authors in due time.

Authors are encouraged to submit code alongside the paper. Authors should provide a readme file explaining how to run the author's software, and, when applicable, how to use it to replicate computational results given in the article. For code that include files not directly relevant to the scientific contribution of the paper, authors should indicate in the readme file which part of the code pertains to the scientific claims of the paper to ease review process.

By default and unless authors specify a different license scheme, the code submitted along the paper will be protected under exclusive copyright linked to the paper ID. Reviewers will be strictly forbidden to use the code outside the review process.

Use of Code / Citation / Licensing
Be aware that you must always cite your sources, including in code you may be using for your research. Failing to do so may lead others to believe that you are the authors of the code, which would be considered as plagiarism. Authors are requested to explicit cite sources in the code header and in the readme file. They must also ensure that, when they modify or use other people's code, they are allowed to do so. See for information on how to act when you find code on the web that does not have a specific license.