[Meetings] [CfP] 2nd Call for Papers & Speakers Announcement: CoRL 2024 Workshop “CoRoboLearn: Advancing Learning for Human-Centered Collaborative Robots”

[raffa...@gmail.com]

Dear all,

We remind you that the October 4th deadline for submitting your contributions to the full-day workshop “CoRoboLearn: Advancing Learning for Human-Centered Collaborative Robots” is approaching fast. We are also pleased to announce our final invited speakers list (see below). The workshop will take place as part of CoRL 2024 on November 9th in Munich, Germany.

This workshop aims to bring together the robot learning and human-robot interaction communities to discuss the specific challenges and opportunities in advancing learning-based human-centered cobots. Invited and spotlight talks, a poster session, and a panel discussion will provide participants with an up-to-date view on open challenges and recent advancement in the field and opportunities for interactive discussions.

We solicit the submission of papers covering recent or ongoing work and early results on the workshop's themes, to be presented during an interactive poster session and selected spotlight talks.

Full description, updates, and details are available on the workshop website: https://sites.google.com/view/corobolearn

Important Dates

• Submission deadline: October 4th, 23:59 Anywhere on Earth (AoE)
  

• Notification of publication decision: October 25th

• Final version due: November 1st, 23:59 Anywhere on Earth (AoE)

• Workshop: November 9th (full day)

Abstract

Collaborative robots (cobots) are designed to work alongside humans in shared environments, distinguishing them from traditional robots that operate in isolation. The defining trait of cobots is their ability to interact safely, efficiently, and intuitively with human partners, adapting to dynamic and uncertain environments. Recent advancements in learning-based systems propelled progress in enhancing such interactions, yet the seamless integration of cobots into everyday environments remains a significant challenge. This workshop aims to bring together leading experts from the robot learning and human-robot interaction communities to discuss the specific challenges and opportunities in advancing learning-based human-centered cobots.

Workshop Topics

The workshop will focus on, but is not limited to, the following guiding topics:

Key Challenges in Human-Centered Collaboration:

• What are the primary obstacles when deploying cobots in human-centric environments?

• What are the unique benefits and challenges of using learning-based approaches for human-centered collaboration?

Learning to Adapt and Improve in Real-World Situations:

• How can cobots leverage information from humans and the environment to learn and adapt their actions in real-time?

• Which approaches can ensure continual learning and adaptation in collaborative tasks?

Innovative Learning Methods and Intuitive Interfaces:

• How can recent progress in generative AI, such as foundation models and LLMs, be leveraged to enhance the capabilities of cobots in human-centric environments?

• How can we utilize new communication interfaces (e.g., wearables and gestures) to ease and enhance human-robot interaction? 

Simulation and Real-World:

• What are the pros and cons of learning from real-world data compared to simulated data for collaborative tasks? How to effectively model human behavior in simulation?

• What are the potential approaches to bridge the sim-real gap for collaborative robotic tasks?

Submission Instructions

Papers covering ongoing work, under peer review, or published recently (including in the CoRL 2024 main conference track), are welcome. There will be no proceedings for this workshop.

Paper submission format:

• Format: CoRL conference paper template

• Open Review submission page

• Submissions must be anonymous, since papers will be peer-reviewed in double-blind mode. This includes potential links to supplementary videos and repositories. Submissions and reviews will not be released publicly.

• Paper length: 4 to 8 pages, excluding references, acknowledgments, and appendices

Accepted papers will be presented in-person during an interactive poster session, and selected papers will also be presented as spotlight talks. 

At least one of the authors needs to be present at the venue for each paper. Accepted papers will (optionally) be made available on the workshop website.

More details on the submission process are available on the workshop’s website.

Invited Speakers

• Andrea Bajcsy
  Assistant Professor in the Robotics Institute and School of Computer Science, Carnegie Mellon University, USA
  Website
  

• Dongheui Lee
  Full Professor of Autonomous Systems at Institute of Computer Technology,
  Faculty of Electrical Engineering and Information Technology, TU Wien, Austria
  Website

• Gerhard Neumann
  Full Professor
  Karlsruhe Institute of Technology, Germany
  Title: “Methods and Intuitive Interfaces for Integrating Human Feedback in Robot Learning”
  Website
  
  

• Daniele Pucci
  Researcher (Tenure Track) - Principal Investigator
  Istituto Italiano di Tecnologia, Genoa, Italy
  Title: “Towards Shared Embodied Intelligence”
  Website
  
  

• Jiajun Wu
  Assistant Professor
  Stanford University, USA
  Title: “Human-Centered Robot Learning”
  Website
  
  

• Davide Scaramuzza
  Professor and Director of the Robotics and Perception Group
  University of Zurich, Switzerland
  Title: “Reaching the limits in autonomous racing”
  Website
  
  

• Fanny Ficuciello
  Assistant Professor in Robotics and Automation - Prisma Lab
  University of Naples Federico II, Italy
  Title: “Autonomous Manipulation Combining Reinforcement Learning and Gaussian Process Regression for Variable Impedance Control”
  Website
  

Organizing Committee

• Loris Roveda
  Associate Professor @ Politecnico di Milano, Italy
  Senior Researcher @ IDSIA USI-SUPSI, Lugano, Switzerland
  Website
  
  

• Asad Ali Shahid
  Researcher
  IDSIA USI-SUPSI, Lugano, Switzerland
  Website
  
  

• Raffaello Camoriano
  Assistant Professor @ Politecnico di Torino, Italy
  Affiliated Researcher @ Istituto Italiano di Tecnologia, Genoa, Italy
  Website
  
  

• Yue Hu
  Assistant Professor
  University of Waterloo, Canada
  Website
  
  

• Cheng Tang
  Research Assistant
  University of Waterloo, Canada
  Website

Institutional Partners

We would like to thank our institutional partners for their invaluable support:

• FAIR: https://future-ai-research.it/

• ELLIS Unit Turin: https://ellis.eu/units/turin

For any questions, feel free to contact us at: corob...@gmail.com

Best regards,
The organizing committee