• Please contact us if you plan to organize related workshop/special sessions or issues in RAS (co-)sponsored conferences and journals, we are able to support you (financially).
• Please contact us if you have resources (new robotic experiments, open source libraries, new survey papers, etc.) on deformable object manipulation, we will collect them and showcase on our website
• We plan to organize two online talks on deformable object manipulation this year, stay tuned!

The Deformable Object Manipulation (DOM) Working Group aims to advance the development and application of robots for manipulating non-rigid, deformable objects. Our scope encompasses various deformable materials, including textiles, cables, food items, biological tissues, and other soft or flexible materials. The WG will focus on addressing key challenges in the field, such as the perception and modeling of deformable objects, the development of adaptive control strategies, the integration of tactile and force feedback, and the creation of robust planning algorithms for complex manipulation tasks. We will explore the application of cutting-edge technologies, including generative AI, machine learning, soft robotics, and advanced sensing, to enhance the capabilities of robotic systems in handling deformable objects. The working group will serve as a platform for interdisciplinary collaboration, bringing together researchers in robotics, materials science, computer vision, and control theory to share knowledge, identify research priorities, and develop best practices. By fostering innovation in deformable object manipulation, we aim to significantly expand the capabilities of robotic systems across various domains, including manufacturing, healthcare, household robotics, and agriculture, ultimately leading to more versatile and capable robotic solutions for complex real-world tasks involving non-rigid materials.

The motivation behind the Deformable Object Manipulation Working Group stems from the increasing need for robotic systems capable of handling non-rigid, deformable materials with the same dexterity and reliability as humans. While significant progress has been made in the robotic manipulation of rigid objects, the manipulation of deformable objects remains a significant challenge due to their complex dynamics, infinite degrees of freedom, and difficulty in predicting their behavior. This gap in capability limits the application of robotics in many important domains, including textile manufacturing, food processing, medical procedures, and domestic tasks. The potential impact of advancing deformable object manipulation is immense, promising to revolutionize industries, improve surgical outcomes, and enhance the capabilities of assistive and household robots. However, achieving these goals requires overcoming substantial technical hurdles in perception, modeling, and control. This working group is motivated by the potential to accelerate progress in the field by fostering collaboration between experts from various disciplines, sharing best practices, and addressing common challenges collectively. By focusing on deformable object manipulation, we aim to push the boundaries of robotic capabilities, opening up new possibilities for automation and human-robot collaboration in tasks that have traditionally been too complex for robots to handle effectively.

• Develop a comprehensive taxonomy and benchmark suite for deformable object manipulation tasks, including standardized datasets and performance metrics.
• Encourage the community to contribute to open-source libraries of algorithms and software frameworks for perception, modeling, and control of deformable objects, facilitating reproducibility and accelerating research in the field.
• Organize annual workshops and challenges focused on deformable object manipulation, fostering collaboration, and driving innovation in the community.
• Initiate at least one collaborative research project involving multiple institutions, focusing on key challenges such as real-time deformation modeling, adaptive control strategies, and generalizable manipulation skills across different deformable materials.
• Develop educational resources and tutorials on deformable object manipulation, targeting researchers, students, and industry professionals.
• Propose a special issue in a high-impact journal focusing on recent advancements in deformable object manipulation for robotics.

• Jihong Zhu, Assistant Professor, University of York, UK
• Xiang Li, Associate Professor, Tsinghua University, China
• Daniel Seita, Assistant Professor, University of Southern California, the US
• Claire Dune, Associate Professor, Université de Toulon, France
• Adrien Koessler, Assistant Professor, University of Lorraine, France
• Júlia Borràs Sol, Professor, Institut de Robòtica i Informàtica Industrial (CSIC-UPC), Spain

For all questions plase contact the corresponding co-chair: jihong.zhu[at]york.ac.uk