On modelling and handling of flexible materials: A review on Digital Twins and planning systems

Dionisis Andronas, George Kokotinis, Sotiris Makris

Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras 26504, Greece

In this paper a series of studies dealing with flexible material manipulation in aspects of manipulation, modelling and scheduling are discussed. The main purpose of this work is to provide an overview of the existing technologies and their capabilities both in manufacturing and academia, that can be elaborated in autonomous flexible material handling using robotics. The particularities of flexible material handling require advanced control systems for simulating, monitoring and managing the deformation of plies. A simulation model for predicting and defining the status of manipulated fabrics is proposed. Digital representation of the production system, in the basis of Digital Twin, is intended for achieving real-time adaptation. A pioneer control and planning system, interconnected to the digital model, is proposed for orchestrating the manipulation process. Current limitations of the existing technologies in flexible material handling and modelling are outlined and discussed, towards the implementation of a Workcell controller for flexible material manipulation robotic cell.


Model-Based Robot Control for Human-Robot Flexible Material Co-Manipulation

D. Andronas, E. Kampourakis, K. Bakopoulou, C. Gkournelos, P. Angelakis and S. Makris,

Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras 26504, Greece

Despite market importance and growth, manufacturing systems involving flexible materials, textiles and composites remain manual. Challenges related to flexible material deformation highlight limitations of robot cognition during fabric handling. This manuscript presents a model-based closed-loop control framework for seamless human-robot or multi-robot fabric co-manipulation. A mass-spring model is used for simulating ply distortion and generating optimal grasping points’ spatial localization. The model is enhanced with real-time operator’s handling actions, as captured from the implemented perception system. The proposed sensor and model-based controlling framework incorporates robot motion planners either for operator support, through non-rigid object co-manipulation, or synchronization of cooperative robots within fully automated tasks. An experimental setup is used for validating system’s handling cognition during collaborative manipulation.

DOI: 10.1109/ETFA45728.2021.9613235

Dexterous textile manipulation using electroadhesive fingers

Krishna Manaswi Digumarti; Vito Cacucciolo; Herbert Shea

École Polytechnique Fédérale de Lausanne (EPFL)

Handling of fabric is a crucial step in the manufacturing of garments. This task is typically performed by trained workers who manipulate one sheet at a time, thus introducing a bottleneck in the automation of the textile industry. This paper seeks to address the challenge of picking fabric up by proposing a new method of achieving ply-separation. Our approach relies on a finger-tip sized (2 cm 2 ) electroadhesive skin to lift fabric up. A pinch-type grasp is then used to securely hold the separated sheet of fabric, enabling easy manipulation thereafter. The ability to successfully pick up and manipulate a variety of commercial fabrics with diverse materials, shapes, sizes and textures is demonstrated. The ability to handle fabrics 100s of times larger than the electroadhesive skin is unique to our approach. Additionally, we demonstrate the manipulation of non-flat fabrics, a challenge that has not been previously addressed by electroadhesive approaches. We believe that this method introduces a smarter way of handling flexible and limp materials, showing great potential towards automation of garment manufacturing.


A variable stiffness soft gripper with integrated ion-drag pump

Michael Smith, Krishna Manaswi Digumarti, Vito Cacucciolo, Herbert Shea

École Polytechnique Fédérale de Lausanne (EPFL)


We present a compact, prehensile and soft gripper capable of varying its stiffness on demand, allowing not only grasping but also manipulation of objects. The gripper consists of fluidic chambers within a silicone structure and two electrostatic clutches bonded to opposite external surfaces. Actuation is achieved by pressurizing the chambers using an integrated electrohydrodynamic ‘ion-drag’ pump while simultaneously blocking one of the clutches, causing the structure to bend around and grasp an object. Once the object is grasped, the second clutch is blocked, significantly increasing the bending stiffness of the structure and allowing the object to be manipulated.




Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras, Greece


Despite extensive automation in multiple industrial sectors, manufacturing operations involving deformable objects are mostly performed manually. Challenges originating from flexible objects’ dynamic distortion underline handicaps in robot cognition and dexterity. This paper presents a model-based motion planner for deformable object co-manipulation. The developed closed-loop controlling framework interprets manipulation inputs into appropriate handling actions by simulating fabric’s distortion through a mass-spring model. The planner incorporates tools for rapid system commissioning and reconfiguration, grasping point planning, and monitoring of human actions. Inspired by automotive composite industry, two experimental setups are used for validating the system’s performance during translational and rotational co-manipulation.