Workshop on Managing deformation: A step towards higher robot autonomy

Managing Deformation in Robotics

A trailer video for IROS 2020 workshop on Managing Deformation: A Step Towards Higher Robot Autonomy

practical Information

Please register for our Live Session on Monday Oct 26 CET (CDT 10:00AM, EDT 11:00 AM, PDT 8:00 AM, JST 0:00 (27th), HKT 23:00PM):

IEEE/RSJ International Conference on Intelligent Robots and Systems

Please note the that IROS is going "On-Demand" this year and will be completely free. The registration link:

aim and scope

The ability to interact with deformable objects of any scale is a prerequisite for advanced robot autonomy. Depending on the size of the object, the development of these skills may involve all the degrees of freedom of one or more robotics systems, and even the mobility of an active platform. These skills are necessary in multiple fields, ranging from grasping and handling of everyday objects (food, clothing, etc.) in consumer robotics, surgical robotic procedures (manipulating tissues, guiding flexible needles, etc), picking up of agricultural products, or movement of large flexible objects (such as cables, ropes, and tents).

However, taking into account deformation introduces new challenges, in particular:

  • The complication of sensing deformation

  • The curse of infinite dimensionality of the deformation configuration

  • The complexity of high nonlinearity in modeling the deformation

New paradigms are needed to address these challenges. Therefore, the aim of this workshop is to discuss new research prospects considering the object’s deformation in various robotic applications.

We can sense deformation with different modalities, e.g. force/tactile measurements provide crucial information for grasping and manipulation, but, this feedback is only locally available. Vision, on the other hand, offers a global picture of shape deformation but is subjected to noise and occlusion. We seek

  1. Methods to robustly sense deformation;

  2. Compact feedback features for characterizing deformation to address the problem of infinite dimensionality;

  3. Exploiting environmental contacts for reducing the deformation dimensions, is another possible direction;

  4. Data-driven/model-based/hybrid approaches to model deformation for control, to cope with the high nonlinearity problem.

We propose this interactive workshop to present and discuss new perspectives in managing deformation as a step towards higher robot autonomy. The purpose of the workshop is to bring together researchers who have common interests in working with deformable objects in robotic applications. The previously-presented challenges and possible directions of research are not exhaustive. The organizers encourage participants to propose new challenges and solutions in the scope of managing deformation.

Topics of interest

  • Deformation sensing

  • Compact representation of deformation

  • Learning/identification/simulation of deformation

  • Multi-contact planning for deformation

  • Application-oriented research (agriculture, household, surgical, industrial)


The workshop is supported by the following IEEE/RAS TCs:

  • Computer & Robot Vision

  • Robotics Research for Practicality

  • Collaborative Automation for Flexible Manufacturing

  • Agricultural Robotics and Automation

  • Robot Learning

  • Mobile Manipulation

  • Algorithms for Planning and Control of Robot Motion

  • Robotic Hands, Grasping and Manipulation


  • Jihong Zhu, TU Delft/University of Montpellier, the Netherlands/France

  • Andrea Cherubini, University of Montpellier, France

  • Claire Dune, Université de Toulon, France

  • David Navarro-Alarcon, The Hong Kong Polytechnic University, Hong Kong