[robotics-worldwide] [meetings] Call for Contributions to the RSS 2020 Workshop "Closing the Academia to Real-World Gap in Service Robotics"

Maru Cabrera mecu at cs.washington.edu
Fri Mar 6 19:53:45 PST 2020


[CALL FOR CONTRIBUTION]

Full-day Workshop at Robotics: Science and Systems 2020
July 13, 2020 - Oregon State University at Corvallis, Oregon, USA

Closing the Academia to Real-World Gap in Service Robotics
Website:
https://urldefense.com/v3/__https://sites.google.com/cs.washington.edu/rss-2020-service-robots/home__;!!LIr3w8kk_Xxm!7XABSDv_pmjO6AQJB9b-o9KWu1etB4ya9NaN3Es2O1dBE4KZoLWeehwi4h29aEMf1mb0VYzH$ 

[ABSTRACT]

Despite increasing commercial demand, progress in learning methods for
robotics, and the decrease in hardware costs, service robots are still far
from helping us. Implicitly or explicitly, the assumptions and the way
experiments are conducted in laboratories lead to research that is
extremely hard to transfer to real use. As a result, scientific research
becomes locked within the university environment while companies must
revisit and re-validate academic work. More often than not, they develop
their own methods to bring robots closer to the market. Our goal is to
bring together experts in academia and industry to uncover issues that so
far have bounded research to the laboratory environment and discuss the
design of methods with potential towards effective, real-world deployment
of service robots.

We envision the achievement of two goals: From the academic perspective, to
identify research practices that align with real-world use, increasing
long-term impact and practical value. From the industrial perspective, to
help research scientists outside academia identify academic work with
potential towards technological readiness. Researchers from both industry
and academia will be encouraged to provide their insights to decrease the
technical transfer gap and promote collaboration. We encourage the
submission of both new research as well as short retrospectives that
discuss practical limitations of past papers that the authors wish to
document for future readers.

[CONTRIBUTING]

We invite several types of contributions:

Full-length paper: 8 pages max (excluding citations)
Position paper: 8 pages max (excluding citations)
Short paper: 4 pages max (excluding citations)
Retrospective: 4 pages max (excluding citations)
Paper format: Full RSS paper format.
Submissions are not double-blind
Submission website: https://urldefense.com/v3/__https://easychair.org/conferences/?conf=arwgap2020__;!!LIr3w8kk_Xxm!7XABSDv_pmjO6AQJB9b-o9KWu1etB4ya9NaN3Es2O1dBE4KZoLWeehwi4h29aEMf1lwCk3FT$ 
Please, contact one of the organizers (emails below) if you have questions
regarding the content of your paper.

Note that all technical topics will be discussed under a practical
perspective. Thus, papers are going to be examined for their assumptions
and how applicable the authors believe the presented method is to a real
application.

[TOPICS OF INTEREST (not limited to)]

    *Naive users*
    Human-robot collaboration or interaction with “naive users.”
In-the-wild studies or methods. What assumptions should we make of
end-users, and how realistic are they for real-world use?

    *Safety in physical human-robot interaction*
    How can we guarantee safe interaction in the real world? How can
hardware design or low-cost robotics support safe interaction?

    *Learning from Demonstration and Programming by Demonstration*
    How do we enable real users (who don’t know how to program) to create
and modify robot behavior? Trade-offs on the simplicity vs flexibility of
user interfaces

    *Deep learning for service robotics*
    How do we obtain sufficient data---or reduce the amount of data
required---to apply deep learning based approaches to realistic problems?
How can we close the sim2real gap and leverage simulations effectively?

    *Perception for service robots*
    Realistic sensing at home, in hospitals, etc..

    *Retrospectives on practicality*
    What limitations did you encounter in your previous research that would
be useful to know for those attempting to put the work into practice?

    *Industry research insights*
        . Pressing issues facing real service robots
        . In-house research that academia does not provide
        . Successful and unsuccessful research cases

[IMPORTANT DATES]
    . Submission deadline for papers: April 9, 2020
    . Notification of acceptance: April 16, 2020
    . Camera-ready version: June 15, 2020
    . Workshop: July 13, 2020

[INVITED SPEAKERS]
    . Andrea Thomaz (Diligent, UT Austin)
    . Leyla Takayama (University of California)
    . Takayuki Kanda (Kyoto University)
    . Carlos Celemin (TU Delft)
    . Hironori Yoshida (Preferred Networks)
    . Heni Ben Amor (Arizona State University)

[ORGANIZERS]
    . Guilherme Maeda (Preferred Networks, Inc.) gjmaeda(at)preferred.jp
    . Nick Walker (University of Washington) nswalker at cs.washington.edu
    . Maru Cabrera (University of Washington) mecu at cs.washington.edu
    . Petar Kormushev (Imperial College London)


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