ARWGAP-2020: Closing the Academia to Real-World Gap in Service Robotics RSS 2020. Oregon State University at Corvallis Corvallis, OR, United States, July 13, 2020 |
Conference website | https://sites.google.com/cs.washington.edu/rss-2020-service-robots/home |
Submission link | https://easychair.org/conferences/?conf=arwgap2020 |
[CALL FOR CONTRIBUTION]
Full-day Workshop at Robotics: Science and Systems 2020
July 13, 2020 - Oregon State University at Corvallis, Oregon, USA
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: link will be available in our website => https://sites.google.com/cs.washington.edu/rss-2020-service-robots/home
If you have problems to submit, send the submission as a pdf file directly to one of the organizers (emails below).
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
*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?
*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..
*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)
[CONTACT]
Feel free to contact one of the following organizers if you have questions.
. Guilherme Maeda, gjmaeda@preferred.jp
. Nick Walker, nswalker@cs.washington.edu
. Maru Cabrera, mecu@cs.washington.edu