Beyond Rigidity - Deformable and Articulated Robotic Object Manipulation Workshop

International Convention Center and University of Technology Sydney

13 July 2026, Sydney

Overview

Robotic manipulation of rigid objects has embarked on a remarkable trajectory, as demonstrated by increasingly advanced manipulation skills and real-world deployments. This progress has been enabled by improved perception pipelines, standardized 6DoF rigid object representations, mature planning, and control frameworks. However, real-world environments contain a diverse set of non-rigid objects: deformable ones, such as clothes, cables, food, and articulated ones, such as dishwashers, laptops, drawers, whose shape, topology, and behavior dynamically changes during interaction. Manipulating these objects remains a fundamental open challenge that requires advances across the entire robotic pipeline, from perception and representation to modelling, planning, and control.

This workshop focuses on robotic manipulation of non-rigid objects, with particular emphasis on deformable and articulated ones. We aim to bring together researchers working on complementary approaches that span end-to-end learning systems and modular pipelines, addressing challenges across the entire manipulation process.

The relevance of this workshop stems from the growing need for robots that can robustly operate in unstructured, human-centered, and natural environments, where interaction with non-rigid objects is unavoidable. Progress in this area is critical for applications such as household assistance, logistics, agriculture, healthcare, and industrial automation, where handling deformable and articulated objects remains one of the key bottlenecks to autonomy and real-world deployment. Currently, two dominant paradigms have emerged: end-to-end approaches that aim to learn manipulation policies from large-scale (often teleoperated) datasets, and modular pipelines inspired by the successes of rigid object manipulation. Each comes with distinct advantages and limitations in terms of robustness, generalization, data efficiency, and interpretability. By fostering discussion between researchers from both paradigms, this workshop seeks to identify common principles, open challenges, and promising directions toward scalable and reliable non-rigid object manipulation.



Speakers

  • Yue Wang

    Yue Wang

    University of Southern California

    Yue is an Assistant Professor at University of Southern California at the department of Computer Science, leading the Physical Superintelligence Lab. He graduated from MIT EECS in 2022, advised by Prof. Justin Solomon at the Geometric Data Processing Group. Previously, Yue was a master’s student at the University of California, San Diego. Prior to that, he received my BEng in Computer Science from Zhejiang University.

  • Niko Suenderhauf

    Niko Suenderhauf

    Queensland University of Technology

    He is a Professor at Queensland University of Technology (QUT) in Brisbane and Deputy Director of the QUT Centre for Robotics, where he leads the Visual Understanding and Learning Program. He is also Deputy Director (Research) for the ARC Research Hub in Intelligent Robotic Systems for Real-Time Asset Management (2022-2027) and was Chief Investigator of the Australian Centre for Robotic Vision 2017-2020. Niko conducts research in robotic vision and robot learning, at the intersection of robotics, computer vision, and machine learning. His research interests focus on robotic learning for manipulation, interaction and navigation, scene understanding, and the reliability of deep learning for open-set and open-world conditions.

  • Kris Hauser

    Kris Hauser

    University of Illinois Urbana-Champaign

    Kris Hauser is a Professor in the Siebel School of Computing and Data Science at the University of Illinois at Urbana-Champaign, and Affiliate of the Department of Electrical and Computer Engineering and the Department of Mechanical Science and Engineering. He received his PhD in Computer Science from Stanford University in 2008, bachelor's degrees in Computer Science and Mathematics from UC Berkeley in 2003, and worked as a postdoctoral fellow at UC Berkeley. He then joined the faculty at Indiana University from 2009-2014, where he started the Intelligent Motion Lab, and then joined the faculty of Duke University from 2014-2019. He also has consulted for Google's autonomous driving company, Waymo, from 2019-2023. Prof. Hauser is a recipient of a Stanford Graduate Fellowship, Siebel Scholar Fellowship, Best Paper Award at IEEE International Conference on Humanoid Robots 2015, the NSF CAREER award, and three Amazon Research Awards. He is currently on leave from UIUC, serving as Head of Robotic Intelligence at Samsung Research America.

  • Noémie Jaquier

    Noémie Jaquier

    Noémie Jaquier is an assistant professor at the KTH Royal Institute of Technology, where she heads the Geometric Robot Learning (GeoRob) Lab at the Division of Robotics, Perception and Learning. She received her PhD degree from the Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland in 2020. Prior to joining KTH, she was a postdoctoral researcher in the High Performance Humanoid Technologies Lab (H²T) at the Karlsruhe Institute of Technology (KIT) and a visiting postdoctoral scholar at the Stanford Robotics Lab. Her research investigates data-efficient and theoretically-sound learning algorithms that leverage differential geometry- and physics-based inductive bias to endow robots with close-to-human learning and adaptation capabilities. Noémie is the recipient of a WASP-AI/MLX professorship and a starting grant from the Swedish research council. She received several awards, notably the Best Presentation Award at CoRL’19, Best Paper Award Finalists (IROS’23, ICRA’24), the Hector-Stiftung Preis 2024 from the Heidelberg Academy of Sciences, and AI newcomer of Technical and Engineering Sciences 2023 by the German Federal Ministry of Education and Research.

Schedule

This is a preliminary version of the schedule and may be subject to change.

TimeDescription
8:30Opening Remarks by the Workshop Organizers
8:45Yue Wang Yue Wang University of Southern CaliforniaTBD
9:15Niko Suenderhauf Niko Suenderhauf Queensland University of TechnologyTBD
09:45Coffee Break and Poster Session
10:45Kris Hauser Kris Hauser University of Illinois Urbana-ChampaignTBD
11:15Noémie Jaquier Noémie Jaquier TBD
11:45Roundtable Discussion
12:25Closing Remarks

Call for Papers

We invite the submission of field reports or extended abstracts on the following topics of interest:

  • - Perception: How can robots perceive non-rigid objects using cameras and other multimodal sensors (e.g., tactile, force, and proprioception)?
  • - Representation: How can non-rigid objects be represented; do we learn or deploy model-based representations; how to balance detail and precision with computational complexity?
  • - Modelling and planning: How can we model and integrate non-rigid object dynamics into planning; what role do world models play in non-rigid object manipulation?
  • - Approaches: What are the advantages and shortcoming of different paradigms for manipulation; with particular emphasis on end-to-end and modular ones?
  • - Evaluation and Benchmarks: How to best measure progress; what are common benchmarks, datasets and metrics for manipulating non-rigid objects?

All submitted papers will be reviewed on the basis of technical quality, relevance, significance, and clarity. The page limit of submitted papers is 4 pages including references. We also accept submissions of previously presented work, that you have extended on and work that is being published as part of the RSS 2026 main conference. Upon acceptance, you will be able to present your submission as part of the poster session. All accepted submissions will be available for the workshop on this website (non archival).

Please submit your extended abstracts following the RSS 2026 format guidelines. For details see the following link:

Please submit your workshop paper through OpenReview.

Important Dates

Extended Abstract Submission Deadline: 12 June extended to 19 June, 2026

Decision Notification: 17 June extended to 22 June, 2026 (if earlier notification is necessary due to travel plans, please contact Leonard Klüpfel)

Workshop Date: 13 July, 2026

Organizers