Review
published: 03 October 2017
doi: 10.3389/frobt.2017.00048

Self-Healing and Damage Resilience
for Soft Robotics: A Review
R. Adam Bilodeau1,2 and Rebecca K. Kramer1,2*
1
Purdue University, School of Mechanical Engineering, West Lafayette, IN, United States, 2 Yale University,
School of Engineering and Applied Science, New Haven, CT, United States

Edited by:
Matteo Cianchetti,Sant’Anna School of
Advanced Studies, Italy
Reviewed by:Tommaso Ranzani,
Harvard University, United States
Ali Sadeghi,
Fondazione Istituto Italiano
di Technologia, Italy*Correspondence:
Rebecca K. Kramer
rebecca.kramer@yale.edu
Specialty section:
This article was submitted
to Soft Robotics,
a section of the journal
Frontiers in Robotics and AI
Received: 20 June 2017
Accepted: 07 September 2017
Published: 03 October 2017
Citation:
Bilodeau RA and Kramer RK (2017)
Self-Healing and Damage Resilience
for Soft Robotics: A Review.
Front. Robot. AI 4:48.
doi: 10.3389/frobt.2017.00048

Advances in soft robotics will be crucial to the next generation of robot–human interfaces. Soft material systems embed safety at the material level, providing additionalsafeguards that will expedite their placement alongside humans and other biologicalsystems. However, in order to function in unpredictable, uncontrolled environments
alongside biological systems, soft robotic systems should be as robust in their ability
to recover from damage as their biological counterparts. There exists a great deal ofwork on self-healing materials, particularly polymeric and elastomeric materials that canself-heal through a wide variety of tools and techniques. Fortunately, most emerging
soft robotic systems are constructed from polymeric or elastomeric materials, so thiswork can be of immediate benefit to the soft robotics community. Though the field ofsoft robotics is still nascent as a whole, self-healing and damage resilient systems are
beginning to be incorporated into three key support pillars that are enabling the future ofsoft robotics: actuators, structures, and sensors. This article reviews the state-of-the-art
in damage resilience and self-healing materials and devices as applied to these threepillars. This review also discusses future applications for soft robots that incorporate
self-healing capabilities.
Keywords: soft robotics, self-healing, damage resilience, soft actuators, soft sensors

INTRODUCTION
Soft robots are often inspired by key aspects of biological systems, such as their near-infinite
degrees of freedom, dexterity, environmental adaptability, and power output (Kim et al., 2013;
Rus and Tolley, 2015; Balasubramanian et al., 2016). Taking inspiration from the soft, deformable,
and adaptable bodies found in nature, soft roboticists develop robotic systems with capabilities
beyond those achievable by traditional rigid robots (Pfeifer et al., 2012; Majidi, 2013). Becauseof their materially soft nature, soft robotic technologies are often considered to be potentiallysafer for interaction with humans, both as human-assisting actuators and as wearable sensory
skins (Hammock et al., 2013; Laschi and Cianchetti, 2014; Lu and Kim, 2014; Amjadi et al., 2016;
Abidi and Cianchetti, 2017; Wang et al., 2017). However, in order to be commercially viable foreveryday use in these applications, soft robots should be robust enough to function alongside theirself-healing, damage resilient biological companions (Bauer et al., 2014).
This article reviews current examples of self-healing and damage resilient materials that havebeen integrated into soft robot technologies (actuation, structure, and electronics). This review
also has the goal of showing that there is an open field of research in the future of self-healing,damage resilient soft robots. We exclude from this review the details of the chemistry behind
self-healing materials, as many recent reviews and books are already dedicated to this subject

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Bilodeau and Kramer

Damage Resilience for Soft Robotics(Wool, 2008; Wu et al., 2008; Ghosh, 2009; Hager et al., 2010,2016; Murphy and Wudl, 2010; Ahner et al., 2015; Kuhl et al.,2015; Li and Meng, 2015; Roy et al., 2015; Huynh et al., 2017).
For the purpose of this article, we distinguish damage resistance from damage resilience. We define damage resistance as
the ability to withstand an unexpected external stressor without
damage, i.e., getting hit with a hammer, run over by a car, or
exposed to open flame (Martinez et al., 2014; Tolley et al., 2014).
Soft robots are almost always assumed to be damage resistant,an ideal characteristic for robots intended to function alongsidebiological systems in uncontrolled, unpredictable environments.
We define damage resilience as the ability to be materiallydamaged (permanently deformed through crack propagation,
fracture, mechanical failure, or puncture) and then continuefunctioning. Self-healing is an obvious subset of this overarching definition, yet it is a critical ability for next-generation soft
robots and holds equal importance to general damage resilience.
The idea that robots can self-heal, self-repair, or correct for damage that has occurred like biological systems is a concept that isstill relatively new (Frei et al., 2013), but one that would continue
to distinguish soft robots from their rigid-bodied counterparts(Bauer et al., 2014).
Among the many potential advantages of soft robotic systems
is the opportunity to bypass functional partitions. While
traditional robots are usually comprised of components witha single function (e.g., actuators, sensors, structures, andcontrollers), emerging multifunctional materials are enablingcomponents that can fulfill two or three different functions
simultaneously. In the sections that follow, we review the useof self-healing materials in soft actuators, soft structures, andsoft sensing devices. However, we note that material systems
often appear across these categories as researchers have solved
different functional problems using the same materials. Table 1
provides a summary detailing some of the material applications
and damage resilience systems presented in this review.

valuable qualities for actuation (Choi et al., 2007; Kofod, 2008;
Kornbluh et al., 2009; Brochu and Pei, 2010; Anderson et al., 2012;
Rosset and Shea, 2012; Carpi, 2016; Madsen et al., 2016a; Naficy
et al., 2016). By sandwiching a highly stretchable dielectric layer
between two stretchable electrodes, DEAs operate on a simple
fundamental principle: charging the electrodes causes an attraction that squeezes the elastomer-based dielectric layer in between
them, decreasing the actuator thickness and increasing its area.
DEAs can be solid-state or semi-solid (where either the electrodes
or the dielectric layer have fluidic elements), and their dielectrics
can be made of silicones, acrylic elastomers, and other types ofhighly deformable, non-conductive materials (Romasanta et al.,2015). Very high electric potentials (in the range of kV) are often
necessary to induce significant shape change, despite the dielectric typically being a thin film (<1 mm). For greater details, thereader is recommended these recent reviews (Wang and Qu, 2016;
Zhu et al., 2016; Zhang and Serpe, 2017).
The thin nature of DEAs makes them susceptible to defects
from physical damage and manufacturing imperfections. These
defects are often undetectable until the electric potential is applied(Zurlo et al., 2016), and they can create a continuous conductive
bridge or a sudden spark between the electrodes, effectively
ending the life of the actuator. Since this defect-induced failure
occurs at potentials much lower than required for a generaldielectric breakdown, the whole actuator is rendered useless by asingle flaw. Identifying this critical issue with DEAs, researchers
have begun to search in earnest for effective solutions.

Fault-Tolerant Electrodes in DEAs

Fault-tolerant DEAs are a subcategory of DEAs whose electrodes
are resilient to damage caused by dielectric breakdown orpuncture. The group led by Dr. Qibing Pei has been working forthe past decade to develop “self-clearing” electrodes. They first
demonstrated the basics of this idea in 2007 (Yuan et al., 2007),
but it was not until their pioneering paper in 2008 that they
showed that this type of fault-tolerant electrode could operate
after damage, even with a solid foreign object piercing the entire
actuator (Figure 1A) (Yuan et al., 2008). The researchers madea flexible, stretchable electrode from spray-coated single-walledcarbon nanotubes (CNTs) that degrades locally around any sparkcaused by dielectric breakdown, outside sources of electricity, or
physical piercing. This degradation breaks the local continuity,and therefore conductivity, of the electrode, preventing further
loss of energy through the damaged area, though also locallyincreasing the stiffness of the electrode. Initial results demonstrated self-clearing damage resilient electrodes fabricated byspray-coating onto dielectrics made of acrylic elastomers, andfurther work demonstrated self-clearing CNT electrodes onsilicone dielectric layers as well (Yuan et al., 2010). Silicone as
the dielectric material enables tunability of the speed of theself-clearing response by changing the thickness of the dielectric
layer. Furthermore, the self-clearing electrodes enhance theoverall lifespan of a DEA, operating for tens of thousands ofcycles while experiencing and overcoming periodic breakdowns
during operation (Stoyanov et al., 2013).
Another research group led by Dr. Dorina Opris has
investigated damage resilient DEAs, altering both the electrode

DAMAGE RESILIENT AND SELF-HEALINGSOFT ACTUATIONSoft actuation comes in many forms, using specially designed
mate­rial bodies or systems to convert an energy source into
forces and displacements. Energy sources include (but are notlimited to) electricity and electric fields, magnetic fields, pressurized gasses and liquids, thermal energy, and chemically induced
mass transfer, each capable of providing kinematic motion(Madden et al., 2004; Hines et al., 2017). Though different intheir underlying physics, soft actuators all allow for large strains(sometimes greater than 100%) in a flexible or stretchable material. In this section, we look at the current research that has gone
into making these actuators damage resilient.

Dielectric Elastomer Actuators (DEAs)

Dielectric elastomer actuators are a promising actuation mechanism for soft robots (Gu et al., 2017; Hines et al., 2017). DEAs arecapable of high strain deformations at high frequencies (<1 s),reliable blocking forces, and rapid controllability, all of which are

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DamageresiliencesystemApplication

Active material

Modulus ofelasticity

Damageresiliencemechanism

Damageisolation

Actuators (DEAs)

Carbon nanotubes

N/A

Electrodedegradation–

0–10 sModified PMVS

80–200 kPa

Dielectricbuffering–

Actuators (inflatable)

Kevlar/silicone
composite

0.4 MPa

Elastomerpressure

Electronics (RTLM)

Silicone (PDMS)

1.84 MPa

Encapsulating
elastomerpressure

Actuators (DEAs)

RTLM

N/A

–

Silicone oil

N/A–

9.25 GPa/0.54 MPa–

Joule heating

5–10 minMaterial
elasticity

Physical selfhealing (fluidic
reflow)

Self-healing
stimulus

Recoverytime scale

Recoveredmaterial property

Resilience
cyclesRecoveryefficiency
per cycle

Reference

Area strain

>30

0.99

Stoyanov et al. (2013)

0–10 sArea strain

5

0.99

Dünki et al. (2015)–

0–10 sCurvature change

1–

Shepherd et al. (2013)–

0–10 sConductivity

2

0.99

Li et al. (2016b)

Applied voltage

10–20 sArea strain

1

0.8

Liu et al. (2013)

Voltagereduction

0–5 sArea strain

6

0.99

Hunt et al. (2014)

Tensile strength

3

0.78

Van Meerbeek
et al. (2016)

Low melting
temperature alloy
Wax

68–125 MPa–

Thermal

10–20 minCompressive strength20.9

Cheng et al. (2014)

Electronics (RTLM)

RTLM

N/A

–

Thermal

0–10 sConductivity

2

0.99

Li et al. (2016b)

3Structures (low melting
temperature materials)

Chemical self- Actuators (inflatable)
healing (solid
bonding)
Actuators (hydrogel)S-H polymer

7.85 MPa–

Thermal

25 hContraction force

3

0.98

Terryn et al. (2017a)

S-H elastomers

6–287 kPa

–

UV

30 s

Curvature change

1

0.99

Wallin et al. (2017)

S-H hydrogel

240–770 kPa–

Thermal20 minTensile strength

1

0.99

Liu and Li (2017)

Actuators (DEAs)

S-H elastomer

0.54 MPa–

Thermal72 hArea strain

1–

Li et al. (2016a)

Structure (shape memorymaterial)

Shape memory,
S-H polymer

10–650 MPa–

Thermal5h

Bending load

5

0.75

Nji and Li (2012)

Pressure–

Curvature change>1–

Huang et al. (2010)

10–60 minConductivity

1

0.75

Palleau et al. (2013)15–30 sConductivity

3

0.98

Tee et al. (2012)

30–60 s5 min
24 hConductivity
Conductivity
Fracture toughness

1
1
1

0.96
0.99
0.95

Darabi et al. (2017)
Liu et al. (2017)
Cao et al. (2017b)

0.3–0.4 MPa

Bilodeau and Kramer

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TABLE 1 | Summary of self-healing and damage resilience mechanisms in the current soft robotic literature.

Joule Heating
Electronics (RTLM)

S-H polymer

240 kPa–

ThermalElectronics (composites)

S-H elastomer

0.4–2 MPa–

ThermalS-H hydrogel

0.67–0.8 MPa
0.1 MPa
0.1 MPa–

ThermalPressure

PDMS, polydimethyl siloxane; RTLM, room temperature liquid metal; S-H, self-healing; PMVS, polymethylvinylsiloxane; DEA, dielectric elastomer actuator.

Damage Resilience for Soft Robotics

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Damage Resilience for Soft Robotics

FIGURE 1 | (A) A damage resilient dielectric elastomer actuator (DEA) (via self-clearing carbon nanotube electrodes) is pierced with a foreign object [(A), a] andcan still actuate [(A), b]. (B) A self-healing, silicone oil-based DEA is pierced with a needle. (C) Liquid-metal alloy is used as a self-repairing electrode layer in a DEA.
[(C), a] The electrode is completely severed into two parts via separation of the liquid alloy. [(C), b] Upon application of the high voltage, the active side (a) expands,
but the disconnected side does not (b). [(C), c] The electric potential disparity causes the liquid metal to flow from the active side to the inactive side, repairing theelectrode and activating the rest of the DEA. (A) Reproduced from Yuan et al. (2008), ©2008 John Wiley & Sons Inc. (B) Adapted from Hunt et al. (2014), 2014 AIP
Publishing LLC. (C) Reproduced from Liu et al. (2013), ©2013 AIP Publishing LLC. All figures are used with permission.

materials and dielectric materials to develop fault tolerance.
In one work, a reduced-graphite electrode layer was used toachieve self-clearing (Michel et al., 2012). Although the original conductivity and stiffness of the undamaged electrode washigher than that of the CNT electrodes presented previously(Yuan et al., 2008), the electrode layer self-cleared without
any increase in stiffness. In a separate work, damage resilience
was embedded into the dielectric layer instead of the electrodethrough implementation of a chemically altered polymethylvinylsiloxane silicone. In the high heat of a spark, this dielectric material rapidly reacts to increase the local impedance,
blocking further charge loss through the initial fault (Dünki
et al., 2015).

Two other recent works have focused on harnessing the
intrinsic healing of fluidic systems to build self-healing dielectric
layers and electrodes. Hunt et al. (2014) created a dielectric layerfrom an open-cell silicone foam filled with silicone oil, with anelectrode made out of a solidified carbon grease. When this DEA
was punctured repeatedly with a needle (Figure 1B) or cut withscissors, the DEA rapidly self-healed and continued to function.
Since the dielectric layer was a two-phase system, the dielectric
oil flowed into the damaged sites, restoring the dielectric barrier
between the two electrodes without any loss of flexibility or
actuation potential in the DEA. Liu et al. used room-temperatureliquid metals (the same used in self-healing electronics, see
Self-Healing Electronics for Soft Robotics) to create a highly
deformable thin-film fluidic electrode for a DEA (Liu et al., 2013).
This liquid-metal electrode was able to self-heal from a break
introduced by squeezing the liquid metal out from between two
sections and sealed with the liquid metal’s non-conductive oxideskin (Figure 1C, a). With simple application of the same potential
used to cycle the actuator, the liquid metal mechanically bridged
the electrical block, reconnecting the rest of the electrode andrestoring full functionality to the DEA (Figure 1C, b,c).
Damage resilient DEAs have been demonstrated using a variety of techniques. In the context of soft robotics, however, there
are still challenges to overcome. DEAs made with self-clearing
electrodes often must be operated at a reduced voltage in orderto maintain the viability of the DEA during cyclic use (Stoyanov
et al., 2013). An electric breakdown at higher voltages can cause
catastrophic failure in the elastic dielectric layer, regardless of theself-clearing electrode. Furthermore, due to limitations in prestraining and elastic response of self-healing dielecric materials

Self-Healing DEAs

Moving beyond “fault tolerance,” several other works introduce
fully self-healing systems into DEAs. This has been done by creating both self-healing dielectric layers and electrodes. Yu et al.
(2015) first demonstrated a silicone dielectric elastomer that could
self-seal holes in the dielectric layer created by a high-energy
discharge spark. Li et al. (2016a) developed a highly stretchable,
self-healing silicone elastomer and used it as the dielectric layer
in a DEA to withstand both electrical and physical damage. A flat
sample of the self-healing elastomer was punctured with a hole,allowed to heal for 72 h at room temperature, and then used asa DEA. The damaged site experienced no dielectric breakdown,even with application of an 11-kV charge on the electrodes. This
research was followed up by Madsen et al., who presented awhole family of self-healing, stretchable dielectric silicones foruse in DEAs (Madsen et al., 2016b).

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Damage Resilience for Soft Robotics(Hunt et al., 2014), self-healing DEAs do not experience strains
as large as their non-healing, counterparts. Self-healing DEAs
also take a significant amount of time to heal, compared to theirself-clearing counterparts (Li et al., 2016a). In the future, damage
resilient DEAs might benefit from combining the various methods
employed above: self-clearing or self-repairing electrodes with
self-healing dielectrics, to create fully healing, highly resilient
actuation systems.

was reinforced with polyaramid fibers (Kevlar) dispersed into thesilicone before curing (Figure 2A). This composite pneumatic
arm was punctured with a needle while under positive pressure
and maintained its internal pressure, even after the needle wasremoved (Figure 2A, b–d). Though the reason behind the damage resilience was never fully discovered, the current theory isthat the damage resilience stems from a combination of the polyaramid fibers preventing crack propagation (Geethamma et al.,2005) and the silicone’s natural tendency to self-adhere whenelastically returning to its original molded shape (after removalof the needle). In another recent example, Wallin et al. (2017)
developed a self-healing elastomer-based soft robot, wherein
UV cure elastomer resins were used to stereolithographically
3D print hydraulic actuators. The 3D printing process trappedliquid resin in the elastomer; when the robot was punctured,
the excess resin was able to seal up the holes if given sufficient
UV stimulus (such as direct sunlight).
Terryn et al. (2015, 2017a,b) have taken a different approachto resilient pneumatic actuators by shaping self-healing polymers
into inflatable chambers. In their early work, they molded a single, thin-walled cube out of a thermally responsive self-healing
polymer and demonstrated its inflation capacity, even after
catastrophic failure (Terryn et al., 2015). Although the pneumatic
cube was made out of a stiff polymer (when compared to elastomers), it deformed with a 40% increase in side-to-side dimension
when inflated (Figure 2B, a). To test its self-healing, the cube

Inflatable Actuators

Pneumatic or hydraulic actuators created out of soft elastomericsilicone materials have become ubiquitous in the soft robotics
community (Hughes et al., 2016; Lee et al., 2017). These actuators are made by casting the elastomer to create channels that,when inflated, cause the body to bend (or twist) in a mannerdependent on the channel design. Their soft, highly deformableelastomer bodies inherently resist damage: absorbing impacts,
twisting and compressive loads and more (Martinez et al., 2014),
and can even survive being run over with a car (Martinez et al.,2014; Tolley et al., 2014). There is a key problem with this damage
resistance: like a balloon, if the actuators pop from overpressure
or puncture, they lose all functionality.
Shepherd et al. (2013) presented a potential opportunity tocorrect this deficiency, wherein they demonstrated a pneumatic
actuator that could be punctured with a 14-gauge needle andcontinued to function. The molded silicone elastomer actuator

FIGURE 2 | (A) Damage resilient pneumatic actuator in an uninflated [(A), a] and inflated [(A), b] state. While inflated, the actuator is punctured with a 14-gauge
needle [(A), c], but the actuator remains capable of inflation [(A), d]. (B) First-generation prototype of a self-healing pneumatic chamber. The stiff self-healing polymer
expands when inflated [(B), a], though overpressure leads to a small air leak [(B), b]. After slitting open the pneumatic chamber and allowing both the slit and the airleak to self-heal [(B), c], the chamber was capable of reinflation. (C) A rapid, self-healing, extensible hydrogel undergoing a self-healing test. The material is severed
into two 2 mm segments [(C), a], allowed to self-heal for ~5 min while being mounted into a tensile machine [(C), b] and then stretched over 100 times its original
length [(C), c—with the healed part emphasized by the arrow]. (A) Adapted from Shepherd et al. (2013), © 2016 John Wiley & Sons Inc. (B) Reproduced from
Terryn et al. (2015), © 2015 IOP Publishing Ltd. (C) Reproduced from Jeon et al. (2016), © 2016 John Wiley & Sons Inc. All figures are used with permission.

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was inflated with positive pressure until the chamber popped.
To enhance the failure of the actuator, the cube was also cut
through with a blade before being heated to instigate self-healing(Figure 2B). After undergoing this puncture and self-healing
cycle, the cube inflated the same way it did before it received any
damage (both in force produced and displacement achieved).
Most recently, Terryn et al. (2017b) demonstrated that by patterning these cubes adjacent to one other, the extended system
could be utilized as a soft robotic bending actuator capable ofgrasping objects. In another recent work, the researchers utilized
this same self-healing material to create a pneumatically actuatedartificial muscle that can contract over 10% of its length (Terryn
et al., 2017a).
Inflatable actuators have seen initial forays into self-healing
and damage resilience, and these initial works open possibilities
for future development. For example, self-healing inflatablerobots open up possibilities in actuator reconfigurability, as the
inflatable actuator material can be cut and rearranged as necessary. To achieve such goals, the limitations of the state-of-the-art
must be addressed, from long healing times to a need for an
intense source of stimulus for self-healing. Since inflatable actuator systems have yet to show any stimuli-independent healing,
it will be particularly important in future research to integrate
the self-healing stimulus into the soft actuator.

out of the ambient environment (Bai et al., 2014; Chen et al.,2014), ensuring that the actuator is always ready to self-heal.
The high water concentration in hydrogels (when comparedwith the humidity of the surrounding air) can enable hydrogel
polymers to heal much more rapidly than normal self-healing
polymers, as demonstrated by Jeon et al. (2016). However,
one constant challenge that hydrogels face is ensuring thatthey remain sufficiently hydrated. Further advantages gained
through the use of conductive hydrogels will be discussed
briefly in Section “Shape Memory Materials” in the context of
self-healing electronics.

SELF-HEALING SOFT ROBOTSTRUCTURES
Given the goals of environmental adaptability and large degreeof-freedom operation for soft robots, it is not surprising thatstructure is of deep interest to soft robotic design (Bar-Cohen
and Breazeal, 2003; Mazzolai et al., 2007; Case et al., 2016).
Designing with materials that support actuation and sensing is
crucial to enable functionality and adaptability in soft robots.
Passive structures, material backbones that hold together a seriesof actuators and sensors, can easily be enhanced by adding selfhealing functionality (Ghosh, 2009; Li and Meng, 2015; Huynh
et al., 2017). Of particular interest to soft roboticists are stiffnesschanging materials that enable soft robotic structures to have
low stiffness for adaptation or actuation, and high stiffness toincrease output forces or provide stability. A recent review covers
this topic in more detail in its application to soft robotics (Manti
et al., 2016). It is with this idea of structural materials that we
continue our investigation of self-healing and damage resiliencein soft robotics.

Hydrogel Actuators

Hydrogels are a type of extremely hydrophilic thermoset polymer matrix that absorb water molecules into the bulk material.
By pulling water molecules in between the long polymer chains,
a hydrogel’s polymer matrix expands, enabling a change in size
many times that of the original structure. This diffusion-limited
process has been used repeatedly in soft robots as a potential
actuation method (Gerlach and Arndt, 2009; Richter, 2009;
Kim et al., 2013). Self-healing hydrogels are their own field of
research for materials scientists, as can be seen in recent reviews(Phadke et al., 2012; Taylor and Marc in het Panhuis, 2016).
Yet, despite this field of research, hydrogel self-healing has yet
to enter the soft robotics community, so this section is mostly
forward-looking based on presently developed systems.
Responsive hydrogels have not generally been used in
actuators (inflatable or otherwise) like silicones and other inert
elastomers. Yuk et al. recently broke this trend in their novel
application of hydrogels as an inflatable robotic gripper (Yuket al., 2017). The hydraulic gripper was built with a highly
deformable hydrogel that was simultaneously gentle and robust,capable of trapping a live fish without harming it. Highly stretchable, self-healing hydrogels such as the one recently presented
by Jeon et al. (2016) could potentially be used to create thesetypes of hydrogel grippers. Their hydrogel can self-heal very
quickly (in under 30 s, given ideal conditions) and can strainover 1,000% its original length (Figure 2C). Similar work has
recently been presented by Liu and Li (2017) whose tough, selfhealing hydrogel requires slightly more healing time but is also
ionically conductive.
There is much to gain by further exploring self-healing hydrogels in soft robots. For example, by adding hygroscopic ions to
the hydrogel, the hydrogel could self-hydrate by pulling water

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Low Melting Temperature Materials

Materials that have been employed in purely functional structuralcases are primarily those that can undergo phase changes at low
temperatures, such as low melting point alloys (LMPAs) or wax.
This is because the low-temperature phase change alters thematerial stiffness by many orders of magnitude, with relatively
small amounts of energy input. These materials are also ideal for
self-healing, since they can change to a liquid form that readilyflows to fill cracks, holes, or other damage. Once the system has
healed the damage, the materials can be cooled again to restore acontinuous solid body.
Low melting point alloys have been used in variable stiffness applications in order to provide a stiffening or morphable
element in the robot (Nakai et al., 2002; Shan et al., 2013;
Shintake et al., 2015), typically display melting points below
70°C and are solid at room temperature. Dr. Dario Floreano’s lab
has demonstrated the value of LMPAs as self-healing, variablestiffness soft robotic components (Figures 3A,B) (Schubert andFloreano, 2013). The researchers started by showing that thesolid LMPA encapsulated in an elastomer provides structural
stiffness until overloaded, causing the metal to crack and break.
When this happens, the load is removed, allowing the encapsulating silicone to restore its original shape and pushing the6

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FIGURE 3 | (A) A planar variable stiffness material made of a self-healable low melting point alloy microchannel in silicone. Top view [(A), a] and side views in a stiff[(A), b] and soft [(A), c] state. (B) Photographs of a low melting point alloy (LMPA) microchannel that has been fractured then Joule-heated to self-repair, as well as
photographs of an LMPA microchannel in a liquid state showing degradation after 700 strain cycles. (C) Self-healing variable-stiffness fiber comprised of LMPA in acompressive silicone sleeve, with a cross section photo inset. (D) Diagram of self-healing hybrid with shape memory alloy (SMA) coils in a self-healing polymer
exterior [labeled as a shape-memory hybrid (SMH)]. (E) A Self-healing cycle of the hybrid. Pulling the SMH apart [(E), a,b]; Joule heating the SMA to restore shapeand encourage self-healing [(E), c,d]; the SMH after healing [(E), e] and bent to show restoration of material flexibility [(E), f]. (F) Self-healing of an LMPA-foam
composite. Damaging the LMPA-foam composite with scissors [(F), a], showing the damage [(F), b] and resealing the damage [(F), c]. (A,B) Adapted from Schubertand Floreano (2013), © 2013 The Royal Society of Chemistry. (C) Adapted from Tonazzini et al. (2016), ©2016 the authors. (D,E) Reproduced from Huang et al.
(2010) ©2010 Elsevier Ltd. (F) Reproduced from Van Meerbeek et al. (2016), ©2016 John Wiley & Sons Inc. All figures are used with permission.

cracked metal together. By Joule-heating the metal, it melts andreforms a continuous structural system (Figure 3B). Though thisprocess breaks down after several hundred cycles (Figure 3B),
it is possible to completely replace the damaged LMPA. Laterwork advanced this concept by sealing LMPA into a silicone tube
that was pre-stretched (see Figure 3C) (Tonazzini et al., 2016).
The pre-stretched tube added a constant internal compression
to the LMPA, improving the self-healing process when compared
to a system using the exact same setup and materials without the
pre-stretch.
Polyurethane and silicone foams have been previously usedas structural elements in soft robotics, as they are usually easy
to deform, compress well, and often can sustain large extensions(Shimoga and Goldenberg, 1992; Lipson, 2014; Yuen et al., 2014,2016). By impregnating porous foams such as these with lowmelting point materials, variable stiffness materials are formed.
This structure differs significantly from the above examples of
encapsulated LMPA, as the low-melting point materials adhere
to the foam (even in a liquid state) using capillary forces andwetting adhesion. Van Meerbeek et al. (2016) mixed LMPA
into pre-cured silicone to create an open-celled, foam structure(see Figure 3F). Not only does the LMPA provide stiffening to
the foam structure but also enables damage repair by welding
the foam block back together with the LMPA post damage(Figure 3F, c). Mirroring the use of LMPAs, Cheng et al. (2014)
filled a polyurethane foam lattice with wax which they broke
repeatedly though over-compression. This foam–wax structure

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can self-heal back to nearly full-strength by melting the wax,
even after multiple over-compressions. Although not conductive like LMPAs, wax does hold an advantage over LMPA sincecareful tuning of the molecular structure of the wax will separate
out the softening temperature (for physical shape change) fromthe solid-to-liquid phase change temperature (for self-healing).
Characterization and implementation of soft robotic variablestiffness, self-healing structures has only just begun. There ismuch opportunity for research into structural materials thatcan change shape and heal from mechanical damage by phasechanging and reflowing in a soft structure. Finding ways for asoft robotic system to auto-detect damage in a phase-changing
structure and initiate the self-repair process is one possible future
step that could be taken in this area.

Shape Memory Materials

Shape memory materials are a type of material, including both
metallic shape memory alloys (SMAs) and shape memory
polymers (SMPs), that can be plastically deformed from a preprogrammed state and self-return to their programmed shapeupon controlled heating. SMAs and SMPs are common actuator
tools that have been used frequently in soft robotics applications (Ionov, 2011; Albu-Schäffer and Bicchi, 2016; Hou, 2016;Rodrigue et al., 2017), but they have only occasionally been usedas variable-stiffness structural materials (Manti et al., 2016). Theirability to autonomously restore form after plastic deformation

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parallels the motivations of self-healing and damage resilience
as presented thus far. However, since their common use as actuators does not strictly fall into our definition of damage resilience(the plastic deformation is expected during operation), we will
not explore this idea further.
With the common use of SMAs and SMPs as actuators, itwould not be difficult to implement them as reinforcing structural elements in damage resilient soft robots (Kirkby et al., 2008;
Ferreira et al., 2016). Huang et al. (2010) demonstrated the feasibility of this by embedding a coiled SMA wire inside of a semiflexible, self-healing polymer (Figures 3D,E). When the polymer
structure was stretched beyond its fracture limit, the SMA coilprevented the two segments from separating completely. After
failure of the encapsulating polymer, the SMA wire was Jouleheated, simultaneously pressing the two fractured halves of thepolymer together and heating them so that they could self-heal,
thus restoring the polymer flexibility (see Figure 3E, a–f). Xiao
et al. (2010) presented a self-healing SMP which could heal its
surface after being scratched, which has initiated research into
self-healing coatings (Luo and Mather, 2013; Dalmoro et al.,2016; Lutz et al., 2016). SMPs have also been used in two-step
self-healing processes where the SMP can close whole cracks
using the shape memory effect then self-heal the cracks throughinternal chemistry (Nji and Li, 2010, 2012; Rodriguez et al.,2011). Such hybrid systems that allow both crack closure andcrack healing show much promise, though the biggest challenge will be demonstrating this capacity while simultaneously
controlling the soft robot using these same materials. For moredetails on self-healing and shape memory materials, we highly
recommend the first chapter of this book: Li and Meng (2015) or
this recent review: Meng and Li (2013).

chemistry and physics to develop self-healing polymers andflexible electronic components, specifically with a focus on
wearables applications (Huynh et al., 2017). In it, self-healing
polymers find applications in a number of sensory-skin devices
such as flexion sensors (D’Elia et al., 2015), strain sensors(Wu and Chen, 2016), capacitors, supercapacitors, batteries,and solar cells (Wang et al., 2013, 2014; Sun et al., 2014, 2016;
Banerjee et al., 2015; Huang et al., 2015; Zhao et al., 2016). Even
though research into these devices continues, we have yet to see
many integrated into soft robotic systems.
Two different approaches have been taken by researchers todevelop fully self-healing, flexible (and sometimes highly stretchable) electronics implementable in soft robotics. The first uses
room temperature liquid metals encapsulated in a self-healing
structure, and the second uses a composite self-healing bulk
polymer mixed with conductive filler.

Room Temperature Liquid Metal-BasedElectronics

Gallium-based room temperature liquid metals (eutectic
gallium-indium, or eGaIn, and eutectic gallium-indium-tin, or
galinstan, alloys) are often used in highly stretchable and flexible
soft electronics (Dickey, 2016, 2017). Their unique properties
allow for a variety of soft systems to be developed that are notavailable in solid-metal electronics. First, when encapsulated inchannels in a silicone elastomer, the liquid metal flows readily,
maintaining continuity as the channel changes geometry due toexternal extension or compression. Furthermore, when galliumbased liquid metals are exposed to air, the liquid metal forms
a stabilizing oxide layer that prevents unwanted flow (Dickey,2014). These two properties make these alloys ideal for use indamage resilient electronics: the stabilizing oxide prevents the
conductive liquid from leaking out any punctures/holes, but theliquid-like behavior allows it to seal circuit breaks.
The effectiveness of room-temperature liquid metals in damage resilient circuitry was recently demonstrated by Li et al.
(2016b). In this work, liquid metal channels encapsulated in
PDMS silicone were cut and pulled apart, thereby breaking
the circuit (Figure 4A, a). When released, the material elastically
returned to its original form and the liquid metal reconnected
the electrical path (Figure 4A, b). Palleau et al. (2013) used
a self-healing, stretchable polymer as an encapsulating bodyaround a room-temperature liquid metal conductive circuit.
This combination was used in both flexible self-healing wires
and bulk planar materials with liquid-metal channels. The bulk
planar material could mechanically and electrically self-heal after
being separated into two parts (Figure 4B, a,b). Furthermore,
the self-healing enabled reconfigurability in the material, asa 2D electronic pathway could be cut and then reconfigured
into a 3D electrically conductive shape (Figure 4B, c,d). Thispowerful demonstration shows separate self-healing mechanisms for the bulk material and the electrical components,and how to combine the two mechanisms to create a fully selfhealing system.
Though self-healing electronics based on liquid metals havebeen demonstrated in their initial forms, we have yet to see
integration of these demonstrations into more complex devices.

SELF-HEALING ELECTRONICS
FOR SOFT ROBOTICS
For any robot to have closed-loop control, it will require someform of sensory feedback combined with an on-board computer
to control its actuation. Toward this goal, sensory skins have beensought by soft roboticists as their flexibility suggest excellent
integration of complex electronic components into soft-bodied
robots (Lu and Kim, 2014). There is an entire class of materials
and devices with numerous arrays of sensors (or even actuators) designed to be either compatible with human skin so thatthey can adhere to a person (Kim et al., 2011), or be generally
stretchable (McCoul et al., 2016). Integration of self-healing into
electronics that are both flexible and stretchable is key to a fully
controllable, self-healing soft robot.
A simple example of self-healing, flexible electronics comesfrom over a decade ago when Carlson et al. (2006) demonstrated
a flexible sensor skin using standard copper-based electronics
encapsulated in a self-healing polymer. The polymer body wasthin enough to be flexible, but when cracked by over-bending, it
could heal completely. This basic body-healing could not restore
damaged electronic components; however, once the metal-based
sensor was damaged, the sensor ceased to function. Since then,a recent progress report has highlighted work done in polymer
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Damage Resilience for Soft Robotics

to 20%), while also being highly conductive and self-healing. The
untreated material can withstand significantly higher strains, butwhen sufficient conductive filler is added (31% vol) to enablehigh conductivity (10 S/cm), the material’s strain-to-failure is
reduced. Alternatively a self-healing elastomer can be coatedwith a layer of conductive particles, as demonstrated by Cao et al.
(2017a). As long as the conductive coating is aligned during theself-healing process, the material regains its conductivity. It isalso worth noting that the elastomer presented in this work isable to self-heal in seconds (on the same order of magnitude
as hydrogel self-healing, but without the need to be hydrated),
which represents a step forward for self-healing elastomericmaterials.
Conductive hydrogels that are self-healing at room temperature, robust, and elastically stretchable have begun to emerge insimple composite-polymer sensory applications. A common
thread among recent examples is the use of metal ions as a key
to both the self-healing chemistry and the conductive element(Darabi et al., 2017; Lei et al., 2017; Liu and Li, 2017; Liu et al.,2017). Though adding metal ions increases the conductivity of
the hydrogels, researchers have carefully tuned the concentration: too low and the hydrogel does not conduct, too high andeither the flexibility of the hydrogel is reduced or it ceases toself-heal. Cai et al. (2017) took a mixed approach by developing a self-healing, stretchable hydrogel and adding conductive
filler (CNTs), much like the composite elastomers previously
mentioned. This conductive hydrogel composite can self-heal in
60 s and recover 98% of its electrical conductivity (demonstrated
multiple times on the same sample). A third approach to conductivity in self-healing, flexible hydrogels is demonstrated fromprevious work, wherein the polymer network itself provides the
conductivity (Shi et al., 2015).
There are many challenges to overcome as conductive composite soft polymers become more incorporated into damage
resilient soft robotic systems. Though the relative electricalstability of many conductive composite polymers has been demonstrated over a few strain cycles, a long-term fatigue cyclic test
has yet to prove that these materials do not suffer from electricaldrift. The few examples of long-term testing on ionically conductive hydrogels have shown that hydrogel systems can lose water
through evaporation during use outside of a solvent environment,
and when this happens, their performance drops significantly(Cai et al., 2017). Also, hydrogel composites tend to have higher
resistances (greater than 1 kΩ for small samples), limiting their
use to mostly strain sensing rather than conductive pathways. Fora more comprehensive look at self-healing composite polymers(both bulk composites and conductive composites), readers arereferred to these other recent, in-depth reviews/book chapters:
Gibson (2010), Benight et al. (2013), Zhu et al. (2014), Ahneret al. (2015), Zhong and Post (2015), Zhang et al. (2017).

FIGURE 4 | (A) LED integration into a liquid-metal circuit. When the silicone
is cut, the electrical pathway breaks, disconnecting the LED [(A), a].
When the silicone is allowed to return to its original form the liquid metal
reconnects, closing the circuit [(A), b]. (B) A liquid metal circuit embedded
in a self-healing polymer. After being cast into initial shapes, the polymers canbe cut and healed into 2D [(B), a,b] and 3D [(B), c] shapes. If the liquid metalchannel is aligned during this healing, electrical conductivity is also restored[(B), d]. (C) A conductive, flexible, self-healing polymer composite. The
polymer is severed [(C), a] and then allowed to self-heal restoring electricalconnectivity [(C), b]. After healing, the composite’s structural integrity[(C), b inset] and flexibility are restored [(C), c]. (A) Reproduced fromLi et al. (2016b), © 2016 The Royal Society of Chemistry. (B) Reproduced
from Palleau et al. (2013), © 2013 John Wiley & Sons Inc. (C) Reproduced
from Tee et al. (2012), © 2012 Macmillan Publishers Limited. All figures
used with permission.

One potential challenge facing this system is the non-conductiveoxide layer that builds up each time the liquid metal is exposed toair (during multiple self-healing events), which results in overall
decreasing conductance. However, liquid metal oxidation has
also been shown to prevent the liquid metal from leaking during
healing events by creating an encapsulating seal at the locationof failure (Dickey, 2014). Therefore, while highly advantageous
in simple applications, implementation of liquid metal as a selfhealing conductor may be limited in applications where stableconductance is necessary, such as resistive sensors.

Composite Polymer Electronics

A second approach to developing fully self-healing electronicsystems uses conductive polymer composites formed out of aself-healing polymer matrix and a conductive filler. Appropriate
mix ratios can allow for strong electrical conductivity throughthe bulk material, while maintaining the self-healing propertiesof the polymer bulk (Tee et al., 2012; Gong et al., 2013). Any
cut or puncture in the polymer will self-heal, reconnecting the
conductive filler material and rejoining the circuit, much like thematerial demonstrated by Tee et al. (2012) (Figure 4C). In thiswork, a polymer composite was demonstrated that could withstand moderate flexing and twisting (withstanding strains of up

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FUTURE PROSPECTS AND CHALLENGES
There are many open possibilities for the future of self-healing
and damage resilience in soft robotics. Since multifunctional
materials that bridge functional partitions drive innovationin the soft robotics field, it is worth pointing out how the9

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Damage Resilience for Soft Robotics

self-healing materials discussed in the previous sections could
continue to break down functional barriers. Recently, Caoet al. (2017b) demonstrated the use of high-resistive, ionic,
self-healing hydrogels as DEA electrodes, showing how work
toward improving self-healing ionic hydrogels is also improving damage resilience in soft robotic actuation. Likewise, DEAs
have also been used as sensory components in soft electronics(Iskandarani and Karimi, 2012; Xu et al., 2016), so progress madetoward fault-tolerant and self-healing DEAs can also be applied
to soft sensors and electronics. Looking to the future, LMPAs
could potentially be used in place of room-temperature liquid
metals in self-healing soft electronics, thereby adding additional
structural function, although simultaneously introducing
the need for thermal control. Furthermore, using the mixing
techniques already demonstrated in liquid metal-filled silicone
foams (Kazem et al., 2017), current self-healing LMPA foams
could be enhanced by replacing the non-self-healing silicone
elastomer with a self-healing elastomer. These are only a few
examples from the large range of applications for self-healingmaterials that will enhance the innovation capacity in future soft
robotic systems.
Though we have presented materials and work already doneby researchers in the soft robotics field, along with some of thenear-future prospects, there are broad challenges that must be
overcome for this field to continue to grow. While self-healingmaterials are prevalent in the literature, it is not always possible to simply import already-existing materials into the soft
robotics community. For example, we discussed the potentialof using self-healing elastomers and hydrogels in inflatable
actuators (see Inflatable Actuators and Hydrogel Actuators);
however, the materials that are currently available for use are
not the ideal solution. Current self-healing elastomers tend to
rapidly stress-relax (Li et al., 2016a), losing their ability to snap
back to their original form. Despite this, immediate applicationof currently available materials would enable an explorationof how self-healing impacts and improves various facets ofsoft robotics, leading to clearer material requirements for selfhealing elastomers and encouraging research into these materials.
Other challenges that must be overcome include determining
the nature of interfaces between materials, especially those that
may be chemically active and simplifying the synthesis of selfhealing materials for bulk applications (i.e., mass-producing
these materials to enable ubiquitous implementation).

Regardless of the challenges being faced, exciting possibilities
are on the horizon for self-healing soft robots. For example, DEA
rolls and stacks are powerful actuators that are highly susceptible to premature failure from a single manufacturing defect(O’Halloran et al., 2008). Self-healing and self-correcting DEAs
would no longer suffer from this fundamental flaw and provide
future soft robots with hundreds of hours of high-deformation,
high-strength actuation. Recent efforts have shown exciting progress using DEAs to blur the lines between soft robot logic control
and actuation (Wilson et al., 2016). Blending actuation andcontrol in fully integrated self-healing soft robotic systems may
enable a new form of materials based logic where logic and actuation components can be cut apart and physically reprogrammed
without any need for software, similar to other recent developments (Zhang and Soh, 2017). Furthermore, creative applicationsof materials that restore physical continuity could make soft
robotics outperform their biological inspirations. We envisionsoft robots that can not only self-repair, but also leverage selfhealing to enable reconfigurability, whereby parts can be cut apartand reassembled to tune overall function or performance.
In conclusion, the work presented in this review demonstrates the exciting possibilities at the intersection of self-healingmaterials and soft robotics. We expect that as these researchcommunities continue to intermix, emerging soft robots will
have the ability to heal from damage, similarly to their biologicalinspirations. Further, this confluence of material breakthroughs
and novel application will enable the next generation of reconfigurable soft robots with tunable gait, function, and body mor­
phology, all on-demand.

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AUTHOR CONTRIBUTIONS
RB and RK conceived of the review topic and wrote the text.
RB gathered the citation base for the review. Both agree to beaccountable for the content of the work.

FUNDING
RB is funded by a NASA Early Career Faculty award (Grant
No. NNX14AO52G). Any opinion, findings, and conclusions
or recommendations expressed in this material are those of theauthors and do not necessarily reflect the views of the National
Aeronautics and Space Administration.

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