Machine learning approaches are fostering impressive new capabilities for robots. The number of research projects and publications are growing quite rapidly, and ML-based product spending is increasing at a compound annual growth rate of 25%. It is an exciting time, but this rapid expansion is outpacing the definition of consensus and science-based methods of assessing approaches and best practices for applying these technologies. Supporting tools, such as datasets for training and benchmarking, are becoming widely available to assist in the development of ML-based systems, but there is a severe lack of such tools for manufacturing robotics applications.
This workshop will focus on addressing the needs of this important application domain that is significantly under-representing in research publications and support infrastructure. The goals of this workshop are:
The workshop will consist of a combination of invited talks that present user and developer perspectives, a panel discussion to bring out major themes or areas of need, a poster session, and a structured discussion with general participation intended to identify the priorities going forward for forming a community to define protocols, guidelines, metrics, test methods, datasets, and tools that will be useful for maturing the application of ML to manufacturing robotics.
Speakers represent different perspectives of this ecosystem: end users of ML-based solutions, developers of tools and implementors of solutions, researchers who seek ways to leverage existing resources and to present their results based on recognized benchmarks and metrics.
This workshop will feature invited presentations by:
Topics speakers will be asked to address, from their relevant perspectives
We invite submissions of extended abstracts (no more than three pages single-spaced) in the RSS conference template by May 29, 2020 on topics related to the workshop focus, including but not limited to:
All extended abstracts will be reviewed by the members of the organizing committee and notification of acceptance will be provided by April 16, 2020. All accepted contributions will be presented as posters during the interactive sessions.
It is the organizers’ intention to guest edit a special issue of a journal based on the output of this workshop. Contributors may be asked to submit an extended version of their submission for inclusion in the special issue.
All submissions should be sent in PDF format to the email: email@example.com.
Elena Messina, National Institute of Standards and Technology, firstname.lastname@example.org
Holly Yanco, University of Massachusetts, Lowell, email@example.com
Megan Zimmerman, National Institute of Standards and Technology, firstname.lastname@example.org
Craig Schlenoff, National Institute of Standards and Technology, email@example.com
Dragos Margineantu, Boeing Research and Technology, firstname.lastname@example.org
For further information please contact the organizing committee at email@example.com.