[I-RIM ML] [CFP] [Workshop] [ERF2024] Call for Contributions - ERF 2024 Workshop "Towards Efficient and Portable Robot Learning for Real-World Settings"

[Roberto Meattini]

------------------------ Apologies for possible multiple postings ------------------------

Call for Papers

"Towards Efficient and Portable Robot Learning for Real-World Settings"

Workshop at European Robotics Forum 2024

https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202311171738220112859&URLID=9&ESV=10.0.19.7431&IV=C241E1EC38B1960DE6E961D190A63AA2&TT=1700242704571&ESN=Mej500%2Bmw9srN5rn2uk2CHEXhvOvo0I8w2RJzRB%2Bdzw%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cHM6Ly9zaXRlcy5nb29nbGUuY29tL3ZpZXcvZXJmMjAyNHdzcmw&HK=8416471915F7F615FB1A0F2178F10C3ED3AB17DF176D9CE4C7373EE886DE6814

SUBMISSIONS ARE OPEN!

Accepted contributions will be published in the

Springer Proceedings in Advanced Robotics

with Series Editors: Bruno Siciliano, Oussama Khatib.



IMPORTANT DATES

Submission Deadline: December 15, 2024

Acceptance Notification: January 15, 2024

Conference date: March 13-15, 2024

Workshop date: TBA

SUBMISSION

Contributions (maximum of 5 pages, single-column, in PDF format, maximum 10 MB) must be submitted in standard Springer Proceedings in Advanced Robotics (SPAR) format, which is available at this link<https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202311171738220112859&URLID=8&ESV=10.0.19.7431&IV=06D183041B16F962ACA3F45CEFD80037&TT=1700242704571&ESN=m78lmuywfpFHm3rOk6lDft388AdSGzgXH%2BBhu%2BhGs%2Bg%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cHM6Ly93d3cuc3ByaW5nZXIuY29tL3VzL2F1dGhvcnMtZWRpdG9ycy9jb25mZXJlbmNlLXByb2NlZWRpbmdzL2NvbmZlcmVuY2UtcHJvY2VlZGluZ3MtZ3VpZGVsaW5lcw&HK=7E6D4397129AC37B46D0C8CA7C995E861E220B6946C711B47BB5D98F915DA485> with the Latex and Word templates. The authors' guidelines for the preparation of contributions come with templates.



Papers submission link can be found at the workshop's website<https://es.sonicurlprotection-fra.com/click?PV=2&MSGID=202311171738220112859&URLID=7&ESV=10.0.19.7431&IV=A1149BA8E1ED66514CEAFBF4670A44B6&TT=1700242704570&ESN=3I7PvKuqNXDEzpt10dZPmymCdqSXlMT86rqxiDJxNSU%3D&KV=1536961729280&B64_ENCODED_URL=aHR0cHM6Ly9zaXRlcy5nb29nbGUuY29tL3ZpZXcvZXJmMjAyNHdzcmwvY2FsbC1mb3ItcGFwZXJzP2F1dGh1c2VyPTA&HK=7B6D6CC93BAD9BDB5CFB786B4149F09F8989264CF799D8B42D1D843A2324A673>.

AIMS AND SCOPE

The next generation of robotic manipulation systems will witness an increase in skills thanks to novel AI paradigms, enabling them to handle complex tasks in unstructured environments and adapt to unexpected circumstances. For autonomous robotic systems to be relevant in practical real-world applications, the learning process must be both data efficient and safe, leveraging on a priori knowledge and models about the environment and tasks. This includes the vital ability to transfer skills between applications and robotic systems while ensuring constant safety under all conditions.

By facilitating discussion among invited speakers, participants, and authors of contributed papers, the workshop aims to study and discuss the following fundamental open research questions:

  *   How can we take advantage of robotic priors, scene structure, and demonstrations to accelerate robotic learning?
  *   How can control theory be integrated into the learning framework to enforce system theoretic properties?
  *   How can a robot efficiently acquire the skills needed for purposeful and high-performance manipulation?

  *   How can we ensure safety when the robot agent needs to physically explore an unknown environment?
  *   How can we minimize the reliance on real-world data in the learning process?

TOPICS

The topics of interest include but are not limited to:

  *   Safe Robot Learning
  *   Transfer learning
  *   Sim-to-Real Transfer
  *   Learning from demonstration
  *   Active Learning
  *   Learning Control
  *   Skill composition and decomposition
  *   Hierarchical learning and planning
  *   Physics-informed machine learning
  *   Model-based reinforcement learning
  *   Residual Learning
  *   Data-Efficient Learning


ORGANIZING COMMITTEE

Dr. Riccardo Zanella, University of Bologna, Italy

Dr. Roberto Meattini, University of Bologna, Italy
Ashok M. Sundaram, German Aerospace Center, Germany

Dr. Nestor Garcia Hidalgo, Eurecat Technology Center, Spain


--
Roberto Meattini, PhD
Junior Assistant Professor
DEI - Department of Electrical, Electronic and Information Engineering
LAR - Laboratory of Automation and Robotics
Alma Mater Studiorum - Università di Bologna
Viale del Risorgimento, 2, 40136 Bologna, Italy
unibo.it/sitoweb/roberto.meattini<https://www.unibo.it/sitoweb/roberto.meattini2/en>
unibo.it/sitoweb/roberto.meattini/en<https://www.unibo.it/sitoweb/roberto.meattini2/en> (english)
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