The field of robotics has experienced significant growth through the integration of machine learning models, particularly with the rise of foundation models, neural-symbolic AI, generative models (such as large language models and diffusion models), and other emerging techniques. While these methods have transformed areas like computer vision, natural language processing, and computer graphics, their application in robotics remains largely underexplored.
This workshop will address this emerging area by bringing together leading researchers and practitioners in robotics to share insights on the latest advancements, methodologies, and best practices. It will feature invited talks from academic and industrial leaders and technical paper presentations discussing groundbreaking approaches and robotic systems that leverage foundation models and neural-symbolic AI. The workshop will also explore current challenges, future research directions, and promote interaction through poster sessions and spotlight talks.
Call for Workshop Papers
We invite submissions for this upcoming workshop, focusing on foundation models, neural-symbolic AI, generative models, and their applications for robotics. The covered topics strictly align with the recent IJRR Special Issue on “Foundation Models and Neural-Symbolic AI for Robotics”.
- Submission site opens on Feb 1, 2025, closes on Mar 2, 2025; Notification on Apr 6, 2025; Camera-ready on Apr 20, 2025; Pacific Time (PT).
- Format: 4 pages excluding acknowledgement, references, and unlimited appendix. Please use the ICRA’25 main conference template (IEEE conference style).
Our primary goal is to foster meaningful discussions and idea exchanges between workshop paper authors and the invited speakers. Therefore, we only accept 4-page short papers, which will not be considered formal publications. Authors may therefore either submit their summarized recent published/accepted results (E.g., IJRR, TRO, and venues selected by roboranking.org) or new ideas with preliminary and unpublished results. This policy allows authors to further develop or resubmit their work to other top-tier venues. Accepted workshop papers will be archived at OpenReview and will be promoted to a broader audience through various media channels.
Please note that we use OpenReview for paper reviewing, but reviewer comments will remain confidential, similar to a traditional review process. The reviewing will be single blind. All authors of accepted workshop papers will be required to present their work in a poster session. Authors of outstanding submissions will be invited to deliver an oral presentation during the seminar listed below. Best paper awards will be presented by the IEEE RAS Technical Committee (TC) on Computer & Robot Vision (CRV). To be eligible for these awards, authors must join the IEEE RAS TC on CRV (which is free) through the IEEE Membership Portal.
Seminar Day 1
Session 1 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Welcome message by organizers & overview of workshop |
TBD |
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Professor California Institute of Technology |
Neuro-symbolic AI for Safety-Critical Agile Control |
TBD |
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Assistant Professor Harvard University |
Generalizable Foundation Models through Compositional Generation |
TBD |
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Coffee Break and Poster Session
Session 2 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Assistant Professor Stanford University |
Data Curation for Robotics Foundation Models |
TBD |
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Associate Research Professor Carnegie Mellon University |
Combining neural representations with rule-based reasoning for autonomous drone search |
TBD |
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Associate Professor Seoul National University |
TBD |
TBD |
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Lunch
Session 3 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Ph.D. student Stanford University |
Task Representations for Open-World Robotic Manipulation |
TBD |
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Assistant Professor King’s College London |
TBD |
TBD |
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Coffee Break and Poster Session
Session 4 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Associate Professor Massachusetts Institute of Technology |
Neuro-Symbolic Reasoning for 3D Spatial AI |
TBD |
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Assistant Professor Georgia Institute of Technology |
Generative Task and Motion Planning |
TBD |
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Research Scientist Bosch Research |
TBD |
TBD |
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Seminar Day 2
Session 1 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Assistant Professor Georgia Institute of Technology |
TBD |
TBD |
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Assistant Professor Stanford University |
TBD |
TBD |
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Coffee Break and Poster Session
Session 2 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Assistant Professor University at Buffalo |
Self-supervised Neural-Symbolic Learning Framework for Robot Autonomy |
TBD |
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Assistant Professor Stanford University |
TBD |
TBD |
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Lunch
Session 3 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Assistant Professor Princeton University |
Foundation model-powered robots that know when they don't know |
TBD |
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Assistant Professor Columbia University |
TBD |
TBD |
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Assistant Professor University of Pennsylvania |
Tapping Foundation Models for Rewards, Representations, and Policies |
TBD |
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Coffee Break and Poster Session
Session 4 (TBD)
Presenter | Session Title & Slides Link | Time | YouTube Link | |
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Assistant Professor University of Michigan |
Dexterous Robots in the Age of Foundation Model: Tactile, Language, and Gestures Representations |
TBD |
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PhD candidate Massachusetts Institute of Technology |
TBD |
TBD |
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Workshop Registration
Workshop Organizers & Committee
Assistant Professor University at Buffalo |
Assistant Professor King's College London |
Assistant Professor Georgia Institute of Technology |
Assistant Professor Stanford University |
Assistant Professor Columbia University |
Associate Professor Seoul National University |
Research Scientist Bosch Research |
President Centaur AI Institute |
Student Organizers
Ph.D. student University at Buffalo |
Ph.D. student University at Buffalo |
Ph.D. student Carnegie Mellon Uni. |
Ph.D. student University at Buffalo |
Ph.D. student University at Buffalo |
Ph.D. student University at Buffalo |