Manufacturing self-healing soft robots with integrated sensors

Research output: ThesisPhD Thesis

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Abstract

Robots and humans are working closer and closer together: in
factories, in our households, and even during surgeries in which
they enter our body. Safety has always been a major concern for
human-robot interaction.1 Moreover, when this collaboration be-
comes closer, the environment typically becomes less structured.
These aspects are often challenging for traditional robots that
consist of rigid parts, and need extensive control algorithms.
As a solution, soft robots were developed. They often draw
inspiration from nature and consist of soft materials, such as
rubbers. This enables them to bend, stretch and twist around
obstacles. By exploiting material properties, structures can be
designed to fulfil tasks without the need for extensive control.
Thanks to this softness, they are safer when interacting with hu-
mans or fragile objects. However, it also makes them vulnerable.
Moreover, the materials are often not recyclable, making them
less ecological.
A solution was found by mimicking nature. By manufacturing
them out of self-healing polymers, they can recover from damage
and thus ‘heal’. These polymers have proven their merit in soft
robotics during the past few years. However, several research
questions were left unanswered. This work provides an answer
to two main questions. How can we more easily fabricate these
robots and what are the requirements? How can we develop and
characterize different sensors for them? The first question can
be seen as a prerequisite for the second, as the development of
sensors does not only require developing conductive self-healing
polymers, it also requires a way to manufacture these more
complex designs.
After introducing the self-healing Diels-Alder polymer net-
works that are used, an in-depth discussion is given on how they
can be processed more easily compared to previous work. This
not only includes casting, but also the development of fused fila-
ment fabrication for these materials. As they solidify by chemical
reaction during printing, rather than by a physical transition,
optimizing the process requires both modelling and experimental
fine-tuning. It was found that the printed parts have a very low
anisotropy, hereby overcoming an important drawback of this
technique. Using various developed processing methods, several
soft grippers were manufactured that can successfully heal from
large damage.
Also self-healing soft sensors were studied. The investiga-
tion started from the development of a conductive self-healing
composite, and how it is used to create resistive strain and ca-
pacitive force sensors. These sensors are then mechanically and
electrically characterized. It is shown that they can recover their
properties after different types of damage. Finally, these sensors
are implemented in a demonstrating application.
Original languageEnglish
Awarding Institution
  • Vrije Universiteit Brussel
Supervisors/Advisors
  • Vanderborght, Bram, Supervisor
  • Van Assche, Guy, Co-Supervisor
Award date4 Jul 2023
Place of PublicationBrussels
Publisher
Print ISBNs9789083333045
Publication statusPublished - 2023

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