AUTHORS

LATE-BREAKING REPORTS

Submissions are not yet open.


 

The 14th Annual ACM/IEEE HRI Conference theme is “Collaborative HRI.” The conference seeks contributions from a broad set of perspectives, including technical, design, methodological, behavioral, and theoretical, that advance fundamental and applied knowledge and methods in human-robot interaction.

The Late-Breaking Reports (LBR) venue at HRI provides authors with the opportunity to present cutting-edge and experimental research results to the community. It is also an excellent opportunity for researchers new to the field to participate in the conference.

All LBR submissions will be reviewed in a mutual peer-review process, and published in the companion proceedings of the conference, which will appear in both the ACM Digital Library and IEEE Xplore. Authors will retain the copyright of their work, and can submit it to other venues. LBRs will be presented at a poster session during HRI 2019.

SUBMISSION INSTRUCTIONS

Authors are asked to submit their LBRs as a 2-page article (including references and figures), in IEEE Proceedings templates.

Authors are encouraged to consult prior years’ submissions to understand the format, and can find further guidelines about the HRI conference.

Submit your paper through the “paper submission and review” website.

Publications should be fully anonymized at time of submission. Please see anonymization guidelines.

Due to a tight publication deadline with the publisher, all submitted abstracts should be “camera-ready” at time of submission. In other words: proof read, spell checked, etc.

PEER REVIEW PROCESS

Similar to the previous year, we will employ a mutual peer review process to help ensure all authors receive feedback on their work, and to help encourage and invigorate the HRI community. At least one author of each LBR submission must agree to review two other LBRs. Reviews will consist of a single paragraph and brief questionnaire.

IMPORTANT DATES

1 December 2018 : Submission Deadline

LBR CHAIRS

Hatice Gunes, University of Cambridge, UK
Brittany Duncan, University of Nebraska, USA
Harold Soh, National University of Singapore, Singapore
lbr2019@humanrobotinteraction.org