ICRA-GraspingWS-2: IEEE ICRA 2021 Fullday Wokshop on Bridging the Gap between Data-driven and Analytical Physics-based Grasping and Manipulation II IEEE ICRA 2021 Xi'an, China, May 30-June 5, 2021 |
Conference website | https://sites.google.com/view/icra2021graspingws |
Submission deadline | May 15, 2021 |
Workshop Date | May 30, 2021 |
The goal of this 2nd fullday workshop at IEEE ICRA 2021 is to bring together researchers with different approaches to grasping and manipulation - both from the classical analytical modeling-based background and from the purely data-driven direction. This workshop will include invited speakers and contributed papers.
Scope
Considerable progress in grasping and manipulation has been achieved using approaches that extract complex behaviors from data. Yet, data-driven approaches are mostly assessed empirically and not necessarily complying with physical and dynamical constraints compared to analytical approaches where these constraints can be modeled manually. Besides, application of black-box learning models often results in limited success due to large data requirements, incompetence in yielding physically consistent results, and lack of generalizability to novel cases. Meanwhile, physics-based approaches have also been improved dealing with uncertainty. Yet, simplifying assumptions on, e.g. contact and friction model, stationary environment, are often needed resulting in models that cannot account for variations arising when contact models are rich or environments are unstructured and dynamically change. As neither a learning-based nor an analytic approach can be considered sufficient for complex manipulation tasks with high dimensional state spaces, a continuum between mechanistic and learning models is indispensable, where both domain-specific knowledge and data are integrated synergistically. In contrast to practices based on simple forms of feature engineering, heuristics, and constraints, this workshop is focused on exploring a deeper coupling of learning-based methods with physics and discussing benefits of analytical and data-driven approaches in grasping and manipulation applications.
Submission Guidelines
We welcome the submission of two page extended abstracts describing new or ongoing work. We aim at providing graduate students and early-career researchers with the opportunity to present their research to an international audience.
**Best submissions will be selected for oral presentations during the workshop.
** Selected papers will be invited for full submission in Frontiers in Robotics & AI Journal edited by the organizers.
- Abstracts are limited to a maximum of 2 pages (including references, examples, tables etc.)
- Abstracts must follow IEEE conference guidelines and template (letter paper)
- Authors should specify whether they would like to be considered for oral or poster presentation
- Abstracts not complying with these guidelines may be excluded from the reviewing process
- All questions about submissions should be emailed to: grasping.workshop@gmail.com
** Abstracts must be submitted in PDF format using the submission form before the deadline
Deadlines:
Abstract submission deadline: May 15, 2021
Acceptance notification: May 22, 2021
Final materials due: May 29, 2021
** All deadlines are at 23:59 US Pacific time
List of Topics
- Learning and analytic approaches dealing with the uncertainty or unobservability in sensing and actuation duringgrasping and manipulation process
- Simulation to reality transfer
- Modeling, representation and integration of sensing modalities for grasp and manipulation tasks, e.g. proprio-ceptive, visual, force/torque, tactile, proximity sensing
- Grasping of known, partially known or novel objectsNew quality measures for grasping under uncertainty
- Learning-based approaches for grasp planning and manipulation: e.g. model-based, model-free, data-efficient,multi-task, transfer, meta learning, reinforcement learning, learning from demonstration
- Analytic and hybrid approaches for grasping and manipulation
- Integration of data-driven with physics-based models for grasping and manipulation
- How to model complex (object/hand/scene) interaction dynamics for grasp and manipulation tasksIntegrating learning and control for grasping and manipulation
- Generalization and scalability of approaches to a variety of hands and objects
- Approaches addressing deformable/flexible object manipulation, dexterous grasping and manipulation, in-handmanipulation, bi-manual manipulation, mobile manipulation (e.g. legged, wheeled, aerial, underwater manipu-lation)
Committees
Organisers
- Yasemin Bekiroglu, Chalmers University of Technology, Sweden
- Naresh Marturi, University of Birmingham, UK
- Marc Deisenroth, University College London, UK
- Yiannis Karayiannidis, Chalmers University of Technology, Sweden
- Miao Li, Wuhan University, China
- Florian Pokorny, KTH, Sweden
- Robert Platt, Northeastern University, USA
Publication
All contributed papers will be available and accessible on the workshop website after June 5.
Venue
Venue will be updated soon...
Contact
All questions about submissions should be emailed to grasping.workshop@gmail.com