Human-robot cooperative transport of soft materials:
the draping of carbon fibre parts
Giorgio Nicola, Paolo Franceschi, Enrico Villagrossi
Abstract— Human-robot co-manipulation of large butlightweight elements made by soft materials is a challenging
operation that presents several relevant industrial applications.
This work discusses the approach for human-robot collaborative transport of flexible materials developed within theEU H2020 DrapeBot project. The DrapeBot project aims todevelop a human-robot cooperative system capable of assisting
an operator working on the carbon fibre draping process. Theuse of smart human-robot arbitration algorithms and the online
tracking of material deformation enables a natural humanrobot interaction.
Index Terms— Human-robot interaction; Collaborativetransport; Human-robot arbitration;

I. I NTRODUCTION
The human-robot co-manipulation of soft materials is
becoming a relevant task from the industrial point of view,
such as in aerospace, transport, and maritime industries.
Compared to manipulating rigid materials, it introduces newchallenges in modelling, perception, grasping, and control[1]. The European project DrapeBot1 aims to develop ahuman-robot interaction technology capable of supporting
one single human operator handling large carbon fibre parts
during the draping task [2], which is performed by transporting the fabric onto the preform and adapting its shape.
II. M ETHODSThis research investigates using a 3D camera to measure
the deformation of soft materials (i.e., carbon fibre and fibreglass patches in the DrapeBot project) co-manipulated between humans and robots. The RGBD information, provided
by the 3D camera, is processed through an AI algorithm toestimate the deformation of the material w.r.t. a deformation
setpoint [3]. The material deformation estimation feeds acontrol algorithm able to arbitrate the role of the robot andthe human. The control algorithm exploits the Differential
Game Theory [4] to arbitrate the role of leader and follower
between the human and the robot. For a given robot’s nominal trajectory, the control algorithm allows nominal trajectory
deformations based on the material deformation and thecurrent position of the robot w.r.t. the nominal trajectory.
The human-robot arbitrator dynamically assigns the leaderrole to the human or the robot based on their perceived
interaction, providing a natural interaction and avoiding
unwanted situations. The use of the vision sensor allows for
Giorgio Nicola et al. are with the Institute of Intelligent Industrial
Technologies and Systems for Advanced Manufacturing, National Research Council of Italy, Via A. Corti 12, 20133, Milan, Italy; giorgio.nicola@stiima.cnr.it, https://orcid.org/0000-0001-8173-0707
1 www.drapebot.eu, accessed on 03/01/2023

Fig. 1.

Control architecture description.

measuring the soft material deformation. In contrast, a 6D
force/torque sensor allows only the measurement of traction
forces, while a vision system allows the preservation of thematerial from high forces exerted by the human, avoidingdamage. The control architecture is described in Figure 1.
III. C ONCLUSIONS AND F UTURE W ORKS
The research proposed a control architecture using a 3D
camera to measure the deformation of soft materials andan arbitration algorithm able to change the leader’s role inhuman-robot cooperative material transport. Future works
will test the control architecture described above on a realindustrial application.
ACKNOWLEDGMENT
This research has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No
101006732, ”DrapeBot – A European Project developing collaborative
draping of carbon fibre parts.”

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