SCIENCE ROBOTICS | RESEARCH ARTICLE
SOFT ROBOTS

OmniSkins: Robotic skins that turn inanimate objects
into multifunctional robots
Joran W. Booth1, Dylan Shah1, Jennifer C. Case1,2, Edward L. White2, Michelle C. Yuen1,2,Olivier Cyr-Choiniere1, Rebecca Kramer-Bottiglio1*

Copyright © 2018
The Authors, somerights reserved;
exclusive licensee
American Association
for the Advancementof Science. No claim
to original U.S.
Government WorksINTRODUCTION

Robots are typically designed to perform a finite collection of tasks
in a known context. This approach produces efficient solutions whenthe environment is structured and predictable. However, in many
situations—such as exploration, search and rescue, or operating
alongside humans—knowledge of the task to be performed, or thecontext in which it is to be performed, cannot be known a priori.
One approach to alleviating this problem is the use of soft materials
in robotics (1–3), where material deformation both enables damage-­resilient soft robots (4) and allows simple designs to extend tomultiple motion patterns (5). Soft robots have been shown to beadvantageous for manipulation of delicate objects (6, 7), compliance-­
matched for wearability (8–10), and able to withstand large impact
forces (11, 12). Soft robots have also been shown to achieve multiple
locomotion gaits with the same structure, such as crawling andundulation of elastomeric robots (5, 13) and hopping and rolling of
spherical robots (14, 15). Another soft robot was shown to perform
both locomotion and grasping tasks (16). Multifunctionality insoft robots may be further enabled by modular and reconfigurable
systems (13, 17, 18).
We introduce a soft robot design approach based on active
robotic skins that manipulate soft, deformable bodies from theirsurface. Robotic skins are modular, conformable sheets with embedded sensing and actuation, which may be applied to, removed
from, transferred between, and reoriented on the surface of soft
bodies (e.g., inflatables, foams, and limbs) to impart motion onto
those bodies. This surface-based approach allows any passive soft
object to be turned into an active soft robot (Fig. 1). Three principles
enable multifunctional robot design with this approach: First,
distinct motions may be achieved by reorienting a robotic skin on
the surface of a soft body. Second, distinct motions may be achievedby wrapping a robotic skin around bodies with different properties
and/or morphologies. Third, multiple robotic skins may be used1
School of Engineering and Applied Science, Yale University,10 Hillhouse Avenue,
New Haven, CT 06520, USA. 2School of Mechanical Engineering, Purdue University,
585 Purdue Mall, West Lafayette, IN 47907, USA.
*Corresponding author. Email: rebecca.kramer@yale.edu

Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

in combination and reconfigured to perform different tasks. We
demonstrated sensor-enabled closed-loop control of the robotic skins
independent of specific actuator and substrate material choices. We
further demonstrated transferability of the robotic skins between soft
bodies to accomplish a wide variety of tasks, including an inchworm
robot that was controlled either remotely by an operator or withonboard light sensors, a continuum manipulator that grasped andmoved objects, an upper-body wearable garment that communicatedposture information to a user, and a tensegrity structure that was
surface-actuated using the robotic skins.
RESULTS

Design of robotic skins
Robotic skins are two-dimensional (2D), fully controllable robotic
systems that can deform soft objects from their surface. The objective of this work is to demonstrate the merits of this surface-based
approach, without confining the concept to any one particular
implementation. A large design space exists for robotic skins, which
includes variation in components (actuators, sensors, and substrates),
configuration (layout of components and geometry of the skin), andlevel of component integration. As examples, we fabricated three
implementations of robotic skins.
To show that different components can be used, we fabricated
two implementations in a simple parallel component configuration
but with different actuators and substrates. One of the implementations used pneumatic actuators integrated into an elastomer substrate (8), whereas the other used coiled shape memory alloy (SMA)
actuators integrated onto a fabric substrate (19–21). Both implementations used conductive composite–based capacitive sensors (22).
Because actuator choice dominates the overall performance of arobotic skin system, we refer to these two implementations as pneumatic skins and SMA skins.
To show that different configurations can be used, we fabricateda third implementation in a triangular component configuration.
This implementation included pneumatic actuators, a fabric substrate, and the same capacitive sensors. Triangulation of actuators
produced biaxial strains and therefore accommodated compound
1 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Robots generally excel at specific tasks in structured environments but lack the versatility and the adaptability
required to interact with and locomote within the natural world. To increase versatility in robot design, we present
robotic skins that can wrap around arbitrary soft bodies to induce the desired motions and deformations. Robotic
skins integrate actuation and sensing into a single conformable material and may be leveraged to create a multitude
of controllable soft robots with different functions or gaits to accommodate the demands of different environments.
We show that attaching the same robotic skin to a soft body in different ways, or to different soft bodies, leads todistinct motions. Further, we show that combining multiple robotic skins enables complex motions and functions.
We demonstrate the versatility of this soft robot design approach in a wide range of applications—including
manipulation tasks, locomotion, and wearables—using the same two-dimensional (2D) robotic skins reconfiguredon the surface of various 3D soft, inanimate objects.

SCIENCE ROBOTICS | RESEARCH ARTICLE

curvature host bodies, whereas parallel actuators produced uniaxial
strains and accommodated simpler, single curvature host bodies.
Other possible configurations include multiple robotic skins that
could be overlaid or other nonparallel actuator layouts, such as radial
patterns or Cartesian grids. Further information on the materials,
dimensions, and manufacture of the robotic skins can be found inMaterials and Methods and in the Supplementary Materials.
Reorienting robotic skins on a soft body enabled
distinct motions
The first demonstrated principle of operation is that a robotic skin
may be used in combination with a soft, deformable body, whereattaching the same robotic skin to a soft body in different ways leads
to distinct motions. We show a simple example of this principle byusing a robotic skin with integrated actuation and sensing attached
to a cylindrical foam body. By orienting the actuators along thelength of the cylinder, linear contraction induced bending motion;
by reorienting the actuators orthogonally, radial contraction induced
compression (Fig. 2). Other motion primitives include axial extension, axial contraction, and torsion.
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

Placing a robotic skin on different soft bodies
affected motion
The second principle we demonstrated is that using the same
skin on soft bodies with different dimensions and mechanicalresponses yielded different motions. The motion achieved depends
on the relationship between the dimensions, material properties,
and force capabilities of the skin and the dimensions and stiffness characteristics of the body. We can leverage this codependence of the motion on both the skin’s capabilities and the body’s
mechanical properties to create a variety of motions by reusing
the same robotic skin. This concept is appealing because changing
out the soft body to adjust the robot’s motion is often much simpler
than altering the robotic components (actuators, sensors, andcontrollers).
As an example, we focused on a continuum bending motion. By
wrapping the same robotic skin around cylindrical foam bodies
with different radii, we achieved different maximum deflections orworkspaces. A robotic skin wrapped around a soft cylinder induced
more deflection as the radius of the host cylinder decreased (Fig. 3),
assuming homogeneous material properties and constant curvature
2 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Fig. 1. Surface-based modular robots can turn any soft body into a robotic system. A robotic skin is a modular, 2D soft robot that can be reconfigured on the surfaceof passive, deformable bodies to produce deformations. Robotic skins can be assembled around different soft bodies in different orientations to produce a wide range ofrobotic systems. This class of robots holds potential for applications where operators need highly reconfigurable, lightweight robots to assist in variable tasks.

SCIENCE ROBOTICS | RESEARCH ARTICLE

Fig. 3. Robotic skins perform differently on different soft bodies. Here, soft cylinders of different radii will yield different maximum deflections (workspaces) for abending segment. (A) By comparing the blocked force of the robotic skin actuators with the force required to deflect the soft cylinder, the maximum deflection may be
predicted. The equilibrium points are highlighted in (B). Shaded regions around the means represent 95% confidence intervals.

(23). Further, by comparing the blocked force characteristics of acontraction actuator with the force required to deform the cylinder,
we could predict the maximum deflection of the system. Figure 3A
plots these forces for both the pneumatic and SMA actuators usedin our implementations, as well as two foam cylinders with radii of
31.75 mm (1.25 in) and 44.45 (1.75 in). Figure 3B shows the intersections of the force curves, which indicate the maximum deflections achievable when pairing specific actuators with specific soft
bodies. In our case, displacements of 27.4 mm (41.4° deflection)
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

and 19.2 mm (29.3° deflection) were predicted for SMA actuators
paired with the smaller and larger radius cylinders, respectively.
The above case highlights how a skin-body system can be designed to achieve a desired deformation. However, the skins may
also be used on arbitrary soft bodies where the material properties
are not known beforehand. Further details on the theoretical basis forpredicting the deformation of bending systems composed of robotic
skins and soft bodies with both known and unknown properties canbe found in the Supplementary Materials.
3 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Fig. 2. Operational concept. (A) Robotic skins embed distributed actuation and sensing into a conformable substrate. (B) Robotic skins may be wrapped around soft
bodies to impart motion onto those bodies. (C) Robotic skins may be reoriented on a soft body to produce different forms of motion. (D) Multiple robotic skins can be
combined into larger assemblies to produce complex motions.

SCIENCE ROBOTICS | RESEARCH ARTICLE
continuum robot (Fig. 4, A and B). Design considerations, such as
the number of skins and distance between them, may easily be
modified, as well as the individual performance of each segment of
the continuum robot system by using robotic skins with different
actuators if desired.
Locomotion robots
The robotic skins are capable of producing many modes of locomotion. Here, we show three different gaits achieved by the pneumaticskins: rowing, inchworm, and bodiless inchworm. Additional gaits
are presented in the Supplementary Materials. For all locomotion
gaits demonstrated in Fig. 4, the actuators were pressurized at convenient rates (between 3 and 10 Hz) and pressures (140 kPa). The
rowing gait was generated by attaching a skin to a foam cylinder
with weighted end caps and cycling through the actuators (Fig. 4, C
and D). Locomotion inspired by the inchworm (24, 25) was achievedby wrapping a skin around a foam cylinder with polystyrene “feet”
on the ends (Fig. 4, E and F). We further generated a bodiless inchworm gait, which demonstrates that robotic skins with components
tightly integrated into the substrate may operate independently of ahost body (Fig. 4, G and H). To achieve bodiless inchworm locomotion, we simultaneously and cyclically contracted and then relaxed
all of the skin’s actuators, resulting in repeated arching and flattening of the skin, and forward motion due to biased feet. In all cases,

Fig. 4. Modular robotic skins can be combined and/or reconfigured for various tasks. (A and B) Three robotic skins are linked together to form a continuum robot.
These are then separated into three individual robotic skin modules and used to generate different locomotion gaits: (C and D) rowing locomotion, (E and F) inchworm
locomotion, and (G and H) bodiless inchworm locomotion. (I to L) The three robotic skins are then transferred to a three-fingered grasping end effector, using one robotic
skin per finger.
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

4 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Reconfiguring robotic skins and soft bodies
enabled multifunctionality
The third principle that we demonstrated is that multiple robotic
skins may be used in combination to produce more complex motions and reconfigured for variable tasks (Fig. 4). After completinga task in one configuration, robotic skins can be removed and transferred to a different body to accomplish a different task. We demonstrated a simple case of this transferability by reconfiguring threerobotic skins in combination with various cylindrical foam bodies toachieve three distinct functions. First, the skins were connected inseries on a long foam body to create a multisegment continuum
robot (Fig. 4, A to B). Second, the skins were separated and applied
to new deformable bodies to produce different locomotion gaits (Fig. 4,
C to H). Third, the skins were applied to a three-fingered end effector
to demonstrate grasping (Fig. 4, I to L). These functions—continuum
motion, locomotion, and grasping—were selected because they areoften the building blocks used in complex robotic systems and canbe leveraged to achieve a wide range of combinatorial tasks.
Multisegment continuum robot
By leveraging the bending motions previously described, multiple
robotic skins can work in collaboration on a single body to achieve
more complex motions. We demonstrated this by using threeskins positioned on a long foam cylinder to form a three-segment

SCIENCE ROBOTICS | RESEARCH ARTICLE
the locomotion gait and speed may be modified by tuning the skinbody interaction or parameters of the skin itself.
Grasping end effector
We further used the same robotic skins previously used for the three-­segment continuum robot and three locomotion robots to demonstrate a three-fingered grasping end effector (Fig. 4, I to L). The skins
were attached to foam cylinders bundled together, and high-friction
pads were applied to each fingertip to increase contact friction with
objects. To achieve the grasping motion, each skin bent its cylinder
inward to grasp the object.

time on the order of 4 ms. Further information about the control
algorithms can be found in the Supplementary Materials.

Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

5 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Applications and comparisons to purpose-built systems
Because robotic skins are modular (combinable and separable),reconfigurable (easily removed from, transferred between, and reoriented on host bodies), and fully controllable, they could be used
to “roboticize” a wide variety of soft objects to achieve variable tasks(see Fig. 6 and movies S1 to S6). Single skins could be used for locomotion robots and may be integrated with other elements to create
a complex robotic system. For example, we used a skin affixed to a
Closed-loop control of robotic skins
foam cylinder to create an inchworm robot and further added either
We demonstrated sensor feedback and closed-loop control of systems a camera or light sensors to achieve control by a teleoperator orusing robotic skins (Fig. 5). In our implementations, we controlled control by external light (Fig. 6A). In another demonstration, we
the robotic skins by pairing each actuator with an off-board pressure used robotic skins to create continuum manipulators (Fig. 6B), withor current controller and each sensor with an onboard signal condi- different orientations of the skins being useful for different types oftioning circuit. Sensors and actuators were colocated in pairs and end effectors (movies S1 to S6). Given the planar, conformable nature
can be used to provide direct state feedback, rather than relying on of robotic skins, they also lend well to wearable applications. We
inferential measures such as pressure or motion capture. This direct demonstrated this by affixing robotic skins to an upper-body garmeasurement approach has been enabled by recent advances in large-­ ment. Sensors in the skins detected the posture of the wearer anddeformation strain-sensing technologies (26, 27). The sensors used communicated poor posture (above a sensor output threshold) byin our implementations were made from a silicone composite that pulsing the actuators gently, creating a user-in-the-loop control scheme
relies on expanded intercalated graphite (EIG) to achieve electrical (Fig. 6C). Last, the robotic skins could be combined with complex
conductivity (22). We used this conductive composite as the elec- geometries, such as a six-bar passive tensegrity structure (an icosatrode material to fabricate high-deformation capacitive strain sen- hedron). We used 20 triangular robotic skins, which were also usedsors with a linear relationship between capacitance and length (see in the wearable demonstration and attached at the vertices to coverfig. S8C). Sensor outputs during open-loop inchworm locomotion each of the 20 icosahedron faces, and actuated the skins to inducefor both pneumatic and SMA skins are shown in Fig. 5 (A and B).
rolling locomotion (Fig. 6D).
The sensor information can be used to create sense-plan-act loops.
In the above examples, the resulting robots performed comparably
To demonstrate these loops, we wrapped both the pneumatic and to purpose-built systems. For example, our tensegrity system moved at
the SMA skins around a foam cylinder with a 31.75-mm (1.25-in) a speed of 0.06 body lengths per second (BL/s), compared with otherdiameter. By controlling a single actuator, the robot was commanded six-bar tensegrity locomotion robots that have achieved 0.08 BL/s
to shorten one side of the body in a stair-step pattern (Fig. 5, C and (28) and 0.05 BL/s (29). In calculating tensegrity body lengths, we
D). We were able to consistently control the change in length of one divided the distance traveled over time by rod length, which repside of the cylinder to a resolution of 1 mm, with an initial sensor resents a constant characteristic dimension for these robots. The
length of 90 mm, with both types of skins.
wearable application we show with the robotic skins was able to mimic
The pneumatic skin had its sensors bonded to its contraction-­ the functionality of the posture garments demonstrated in previous
type McKibben actuators (which start in their extended, strain-­ work (30–32) but was less integrated into the shirt, and the placement
limited state), and thus, its sensors can only contract. In contrast, was not optimized for the biomechanics of each specific user. For our
the sensors in the SMA skin were not strain-limited by their corre- locomotion robots, the rowing robot locomoted at 0.6 BL/s (Fig. 4,
sponding actuators. When the SMA skin bent a deformable body, C and D), the inchworm robot locomoted at 0.013 BL/s (Fig. 4, E and F),
the sensor on the outer surface of the curved body was fully pressed and the bodiless inchworm robot locomoted at 0.2 BL/s (Fig. 4, Gagainst the body, therefore giving a reliable measure of the strain in and H). These speeds are comparable to purpose-­built inchworm
the underlying surface. Therefore, in Fig. 5C, we plot the pneumatic robots in the literature, which move between 0.014 BL/s (33) andskin’s set point as a contraction (the skin using an actuator to con- 0.15 BL/s (34), as well as biological inchworms, which move between
tract its underlying sensor), whereas in Fig. 5D, we plot the SMA 0.28 and 0.62 BL/s, depending on the species (35). Body lengths reskin’s set point as an extension (the skin using an actuator to stretch ported here were measured as the length of the body in the direction
its opposing sensor).
of travel. This metric differs between fields, notably biology where
Because we measured the deformation of the surface of a body, the characteristic length between organisms varies by several orders
our control algorithm was not dependent on the material or the of magnitude, and it is sometimes customary to measure body length
dimensions of the underlying deformable body. Rather, the linear as the longest length of the organism (36).
response of the sensors was used to infer the length of the underlying
Our goal in making these comparisons is to demonstrate that the
portion of the skin. For the SMA skin, we implemented a bang-bang robotic skin concept can be used to produce robots with reasonable
control algorithm. For the pneumatic skin, a proportional-integral performance across a diversity of applications. The locomotion
controller was used as an additional control loop to deal with the speeds reported herein are representative of rapidly prototyped sysfaster dynamics of the pneumatic system. The complete actuation tems, and better performance could be achieved through optimizatime of the pneumatic actuators was on the order of 20 ms, relative tion, such as friction optimization between the robot and the surface.
to an actuation time of a few seconds for the SMA actuators. The Further, there are trade-offs between optimization and design “onactuator dynamics are detected by the sensors, which have a sample the fly” as related to force density: A purpose-built robot designed

SCIENCE ROBOTICS | RESEARCH ARTICLE

Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018
Fig. 5. Onboard sensors enable state feedback and closed-loop control of robotic skins. (A and B) Sensor feedback during open-loop locomotion for both pneumatic and SMA skins positioned on soft cylinders. Actuation sequencing is shown in the cross-section schematics. (C and D) The state feedback from the sensors may be
used for closed-loop control of cylinder deflection. Solid lines indicate the set point, dashed lines indicate the mean position, and clouds indicate the 95% confidence
interval, over multiple trials. Five trials are shown for the pneumatic skin and 10 trials are shown for the SMA skin.

for a single task (or finite collection of tasks) could likely use its body
volume to produce greater forces, thereby potentially increasing efficiency but reducing multifunctionality. Our demonstrations emphasize a rapid design approach using reconfigurable robotic skins,
allowing fewer materials and robots to be ported to accomplish awide variety of tasks and, in some cases, retaining comparable function to their purpose-built counterparts.
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018DISCUSSION

Robotic skins produce motions by developing stresses within
deformable bodies. The interaction between robotic skins anddeformable bodies is complex and characterized by two related
phenomena: the transfer of stress from the skin to the body and theresulting mechanical properties of the skin-body system. To effectively produce a deformation, the stresses developed within the skin
6 of 9SCIENCE ROBOTICS | RESEARCH ARTICLE

by the actuators must be transferred into the body. Likewise, toaccurately measure the state of the system, deformations in the bodymust be transferred back into the skin. If the body is too soft, loads
will not be effectively transferred, and the skin will distort the surface of the body without producing bulk movements. If the body is
too stiff, the skin will not generate sufficient stress to produce therequired motion. The exact values of too soft and too stiff are highly
dependent on the application and are under the control of thedesigner when selecting materials and morphologies.
The mechanical properties of the skin-body system are further
influenced by skin design. In our implementations, both the sensors
and the substrates are softer and thinner than the actuators, resulting in small contributions to the overall mechanical system. Rather,
the mechanical properties of the skins are dominated by actuator
choice and configuration, including alignment, areal density, andattachment scheme. There is a continuum of resulting skin-bodyproperties that are available to the designer. At one extreme, for a
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

large stiff body with few actuators sparsely populated within theskin, the system will exhibit properties similar to the body. At theother extreme, for a small soft body surrounded by a skin densely
populated with actuators, the system will exhibit properties similar
to the skin.
Modular, reconfigurable soft robots based on robotic skins havea number of advantageous features. (i) Robotic skins control deformable bodies from their surface, which allows robotic skins to turn
passive, inanimate bodies into active soft robots. The robotic skin
implementations presented here were able to create multiple stablesystem states with millimeter resolution when applied to inert deformable bodies. It is expected that with a set of dedicated deformable body designs and a more elaborate controller, higher precision
could be achieved. (ii) They open the design space for soft robotics.
Rather than designing a single, task-specific system, robotic skins
enable on-the-fly design and production of many systems that perform a variety of functions. That is, in contrast to constructing 3D
7 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

Fig. 6. Robotic skin demonstrations. (A) Inchworm locomotion robots include a camera for teleoperation or light sensors for light control, highlighting potential use
cases in remote locations. (B) Three robotic skins around a soft cylinder form a continuum arm, and a fourth skin between two plates creates a gripper. This continuum
manipulator moves a ball from one location to another. (C) Robotic skins attached to a garment detect poor posture and pulse to communicate with the wearer.
(D) Twenty robotic skins covering the faces of a six-bar tensegrity generate membrane-driven locomotion.

SCIENCE ROBOTICS | RESEARCH ARTICLE

MATERIALS AND METHODS

Details for the fabrication and control of the robotic skins areprovided in the Supplementary Materials. Briefly, elastomer-based
robotic skins were composed of a silicone substrate with McKibben
pneumatic actuators constructed with braided mesh and latex
balloons adhered using tin-cure silicone (Mold Max 10) as a glue.
Fabric-based robotic skins were composed of either coiled Nitinol
SMA actuators or McKibben pneumatic actuators attached at theirends to a spandex substrate. All component combinations of robotic
skins included high-deformation capacitive strain sensors made fromconductive layers of EIG mixed with Dragon Skin 10 Slow Silicone
and dielectric layers of Dragon Skin 10 Slow Silicone. The skins were
Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 2018

controlled using logic controllers. We calculated robot speed resulting from different locomotion gaits as the distance traveled overtime divided by the body length in the direction of travel. We quantified force-displacement characteristics of both the actuators andthe soft bodies by using a materials tester. The theoretical basis forpredicting surface-driven deformation of a soft cylinder, additional
locomotion gaits, and examples of rapid prototyping with robotic
skins are also provided in the Supplementary Materials.
SUPPLEMENTARY MATERIALS

robotics.sciencemag.org/cgi/content/full/3/22/eaat1853/DC1
Text S1. Actuators in robotic skin prototypes.
Text S2. Capacitive sensors and signal conditioning.
Text S3. Robotic skin construction.
Text S4. Predicting deformation of a known object.
Text S5. Predicting deformation of an unknown object.
Text S6. Control algorithms.
Text S7. Locomotion gaits using robotic skins.
Text S8. Rapid prototyping with robotic skins.
Fig. S1. McKibben actuator schematic.
Fig. S2. Capacitive sensor construction and characterization.
Fig. S3. Three robotic skin prototypes that vary in components, configuration, and integration.
Fig. S4. Force versus displacement curves for SMA/McKibben actuators and soft cylindricalbodies.
Fig. S5. A geometric model of a robotic skin deflecting a soft cylinder, with the neutral axis
located along the surface of the cylinder.
Fig. S6. A geometric model of a robotic skin deflecting a soft cylinder, with the neutral axis
located along the center of the cylinder.
Fig. S7. Control algorithms.
Fig. S8. Possible locomotion gaits using robotic skins with and without soft cylindrical bodies.
Fig. S9. Examples of rapid prototyping with robotic skins.
Movie S1. Transferability: continuum robots to locomotion robots.
Movie S2. Inchworm locomotion: teleoperated with camera.
Movie S3. Inchworm locomotion: controlled by light.
Movie S4. Continuum manipulation.
Movie S5. Wearable posture shirt.
Movie S6. Tensegrity ball rolling.
References (37–39)

REFERENCES AND NOTES

1. D. Rus, M. T. Tolley, Design, fabrication and control of soft robots. Nature 521, 467–475(2015).
2. C. Laschi, B. Mazzolai, M. Cianchetti, Soft robotics: Technologies and systems pushing theboundaries of robot abilities. Sci. Robot. 1, eaah3690 (2016).
3. S. Kim, C. Laschi, B. Trimmer, Soft robotics: A bioinspired evolution in robotics.
Trends Biotechnol. 31, 287–294 (2013).
4. R. A. Bilodeau, R. K. Kramer, Self-healing and damage resilience for soft robotics: A review.
Front. Robot. AI 4, 48 (2017).
5. R. F. Shepherd, F. Ilievski, W. Choi, S. A. Morin, A. A. Stokes, A. D. Mazzeo, X. Chen,
M. Wang, G. M. Whitesides, Multigait soft robot. Proc. Natl. Acad. Sci. U.S.A. 108,20400–20403 (2011).
6. F. Ilievski, A. D. Mazzeo, R. F. Shepherd, X. Chen, G. M. Whitesides, Soft robotics forchemists. Angew. Chem. Int. Ed. 50, 1890–1895 (2011).
7. K. C. Galloway, K. P. Becker, B. Phillips, J. Kirby, S. Licht, D. Tchernov, R. J. Wood,
D. F. Gruber, Soft robotic grippers for biological sampling on deep reefs. Soft Robot. 3,
23–33 (2016).
8. Y.-L. Park, B.-r. Chen, C. Majidi, R. J. Wood, R. Nagpal, E. Goldfield, Active modular
elastomer sleeve for soft wearable assistance robots, in 2012 IEEE/RSJ International
Conference on Intelligent Robots and Systems (IROS) (IEEE, 2012), pp. 1595–1602.
9. Y. Ding, M. Kim, S. Kuindersma, C. J. Walsh, Human-in-the-loop optimization of hip
assistance with a soft exosuit during walking. Sci. Robot. 3, eaar5438 (2018).
10. B. T. Quinlivan, S. Lee, P. Malcolm, D. M. Rossi, M. Grimmer, C. Siviy, N. Karavas,
D. Wagner, A. Asbeck, I. Galiana, C. J. Walsh, Assistance magnitude versus metabolic
cost reductions for a tethered multiarticular soft exosuit. Sci. Robot. 2, eaah4416(2017).
11. S. Seok, C. D. Onal, K.-J. Cho, R. J. Wood, D. Rus, S. Kim, Meshworm: A peristaltic soft robot
with antagonistic nickel titanium coil actuators. IEEE/ASME Trans. Mechatron. 18,
1485–1497 (2013).

8 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018soft robots with a tailored functionality, 2D robotic skins may bewrapped around 3D deformable bodies, removed, and then reoriented or transferred to other bodies to complete different tasks.
Soft robots based on robotic skins can be quickly changed to adapt
to changing system resources or requirements. For instance, the samerobotic skins could be used to create robots that locomote, grasp, ormanipulate objects, as we have demonstrated. (iii) This framework
is independent of actuator, sensor, and material choice. As a result,the principles of design and actuation determined with one set ofcomponents will generalize well to other sets, regardless of application area. (iv) Robotic skins are 2D and may therefore be fabricatedby using available printing and textile manufacturing methods. (v)They are compactable and may be stored flat, or folded and placed
into a volume much smaller than their deployed size, making transportation easier. In addition, readily available deformable bodies thatrobotic skins may be positioned on, such as foam or inflatables, arealso compactable and may consume very little volume during storage
or transport. (vi) Systems generated by using robotic skins anddeformable bodies continue to boast the attractive features of soft
robots, such as lightweight and potentially low-cost materials; nonlinear motions resulting from simple controls; and damage resist­ance during impacts, falls, and vibrations. These features make soft
robots more resilient and render them less sensitive to stressful
mission environments. Robotic skins have these properties, along withthe additional features of reconfigurability and multifunctionality.
Therefore, we believe that this class of soft robots represents a step
toward co-robotics and robot operation in the natural world, where
different functions or gaits may be necessary to accommodate thedemands of unpredictable and dynamic environments.
In this paper, we presented a new class of reconfigurable soft
robots based on modular robotic skins that manipulate deformablesoft bodies. We fabricated robotic skin prototypes using different
materials and components, as well as different component geometries, to show the open design space for the robotic skin concept.
We further provided concrete examples of how these skins can turn
inanimate soft bodies into robots. For a given robotic skin, the motions that it can impart onto a soft body are a function of the material properties and morphology of that body (i.e., bulk modulus andstiffness), the orientation of the skin on the body, and the method of
attachment or load transfer from the skin to the body. In this work,
we have focused on the utilization of a small number of robotic skinprototypes to show how they interact with different bodies toachieve a variety of tasks. However, the basic concept of robotic
skins is widely generalizable with different skin designs, different
components, and different host bodies.

SCIENCE ROBOTICS | RESEARCH ARTICLE

Booth et al., Sci. Robot. 3, eaat1853 (2018)

19 September 201831. E. Sardini, M. Serpelloni, V. Pasqui, Daylong sitting posture measurement with a newwearable system for at home body movement monitoring, in 2015 IEEE International
Instrumentation and Measurement Technology Conference (I2MTC) Proceedings(IEEE, 2015), pp. 652–657.
32. C. Mattmann, O. Amft, H. Harms, G. Troster, F. Clemens, Recognizing upper body
postures using textile strain sensors, in 2007 11th IEEE International Symposium on
Wearable Computers (IEEE, 2007), pp. 29–36.
33. S. M. Felton, M. T. Tolley, C. D. Onal, D. Rus, R. J. Wood, Robot self-assembly by folding:
A printed inchworm robot, in 2013 IEEE International Conference on Robotics andAutomation (ICRA) (IEEE, 2013), pp. 277–282.
34. D. Lee, S. Kim, Y.-L. Park, R. J. Wood, Design of centimeter-scale inchworm robots withbidirectional claws, in 2011 IEEE International Conference on Robotics and Automation(ICRA) (IEEE, 2011), pp. 3197–3204.
35. J. Brackenbury, Fast locomotion in caterpillars. J. Insect Physiol. 45, 525–533 (1999).
36. N. Meyer-Vernet, J.-P. Rospars, How fast do living organisms move: Maximum speeds
from bacteria to elephants and whales. Am. J. Phys. 83, 719–722 (2015).
37. F. Daerden, D. Lefeber, Pneumatic artificial muscles: Actuators for robotics andautomation. Eur. J. Mech. Environ. Eng. 47, 10–21 (2002).
38. S.-M. An, J. Ryu, M. Cho, K.-J. Cho, Engineering design framework for a shape memory
alloy coil spring actuator using a static two-state model. Smart Mater. Struct. 21, 055009(2012).
39. J. Case, J. Booth, D. Shah, M. Yuen, R. Kramer-Bottiglio, State and stiffness estimation
using robotic fabrics, in 2018 IEEE International Conference on Soft Robotics (RoboSoft)(IEEE, 2018), pp. 522–527.
Acknowledgments: We acknowledge A. Bottiglio for assistance with photography and media
compilation. Funding: This work was primarily supported by the NASA through the Early
Career Faculty Program (grant numbers NNX14AO52G and 80NSSC17K0553). D.S. was
supported by the Air Force Office of Scientific Research under award number FA9550-16-10267 and by a NASA Space Technology Research Fellowship (grant number 80NSSC17K0164).
J.C.C. was supported by a NASA Space Technology Research Fellowship (grant number
NNX15AQ75H). E.L.W. and M.C.Y. were supported by NSF Graduate Research Fellowships(grant number DGE-1333468). Author contributions: R.K.-B. conceived the project, planned
the experiments, and managed the research. J.W.B., D.S., E.L.W., M.C.Y., and O.C.-C. designed
and built the hardware. J.W.B., D.S., J.C.C., and E.L.W. wrote the control algorithms. D.S. and
J.C.C. developed the models. J.W.B., D.S., J.C.C., E.L.W., and O.C.-C. performed the experiments.
J.W.B., D.S., and R.K.-B. drafted the manuscript. All authors contributed to, and agree with, thecontent of the final version of the manuscript. Competing interests: The authors declare thatthey have no competing interests. Data and materials availability: All data needed toevaluate the conclusions in the paper are present in the paper and/or the Supplementary
Materials. Additional data related to this paper are available from the authors upon request.
Submitted 1 February 2018
Accepted 13 July 2018
Published 19 September 201810.1126/scirobotics.aat1853
Citation: J. W. Booth, D. Shah, J. C. Case, E. L. White, M. C. Yuen, O. Cyr-Choiniere, R. Kramer-Bottiglio,
OmniSkins: Robotic skins that turn inanimate objects into multifunctional robots. Sci. Robot. 3,
eaat1853 (2018).

9 of 9Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 201812. M. T. Tolley, R. F. Shepherd, B. Mosadegh, K. C. Galloway, M. Wehner, M. Karpelson,
R. J. Wood, G. M. Whitesides, A resilient, untethered soft robot. Soft Robot. 1, 213–223(2014).
13. J. Zou, Y. Lin, C. Ji, H. Yang, A reconfigurable omnidirectional soft robot based on
caterpillar locomotion. Soft Robot. 5, 164–174 (2018).
14. K. Kim, L.-H. Chen, B. Cera, M. Daly, E. Zhu, J. Despois, A. K. Agogino, V. SunSpiral,
A. M. Agogino, Hopping and rolling locomotion with spherical tensegrity robots, in2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)(IEEE, 2016), pp. 4369–4376.
15. Y. Sugiyama, A. Shiotsu, M. Yamanaka, S. Hirai, Circular/spherical robots for crawling andjumping, in Proceedings of the 2005 IEEE International Conference on Robotics andAutomation (IEEE, 2005), pp. 3595–3600.
16. A. A. Stokes, R. F. Shepherd, S. A. Morin, F. Ilievski, G. M. Whitesides, A hybrid combining
hard and soft robots. Soft Robot. 1, 70–74 (2014).
17. S. W. Kwok, S. A. Morin, B. Mosadegh, J.-H. So, R. F. Shepherd, R. V. Martinez, B. Smith,
F. C. Simeone, A. A. Stokes, G. M. Whitesides, Magnetic assembly of soft robots with hardcomponents. Adv. Funct. Mater. 24, 2180–2187 (2014).
18. S. A. Morin, Y. Shevchenko, J. Lessing, S. W. Kwok, R. F. Shepherd, A. A. Stokes,
G. M. Whitesides, Using “click-e-bricks” to make 3D elastomeric structures. Adv. Mater. 26,
5991–5999 (2014).
19. B. Holschuh, D. Newman, Two-spring model for active compression textiles withintegrated NiTi coil actuators. Smart Mater. Struct. 24, 035011 (2015).
20. M. Yuen, A. Cherian, J. C. Case, J. Seipel, R. K. Kramer, Conformable actuation and sensing
with robotic fabric, in 2014 IEEE/RSJ International Conference on Intelligent Robots andSystems (IROS 2014) (IEEE, 2014), pp. 580–586.
21. M. C. Yuen, R. A. Bilodeau, R. K. Kramer, Active variable stiffness fibers for multifunctional
robotic fabrics. IEEE Robot. Autom. Lett. 1, 708–715 (2016).
22. E. L. White, M. C. Yuen, J. C. Case, R. K. Kramer, Low-cost, facile, and scalable
manufacturing of capacitive sensors for soft systems. Adv. Mater. Technol. 2, 1700072(2017).
23. R. J. Webster III, B. A. Jones, Design and kinematic modeling of constant curvature
continuum robots: A review. Int. J. Robot. Res. 29, 1661–1683 (2010).
24. A. Ghanbari, A. Rostami, S. M. R. S. Noorani, M. M. S. Fakhrabadi, Modeling and simulationof inchworm mode locomotion, in Intelligent Robotics and Applications, C. Xiong,
Y. Huang, Y. Xiong, H. Liu, Eds. (Springer, 2008), pp. 617–624.
25. R. H. Plaut, Mathematical model of inchworm locomotion. Int. J. NonLinear Mech. 76,
56–63 (2015).
26. J. Case, M. Yuen, M. Mohammed, R. Kramer, Sensor skins: An overview, in Stretchable
Bioelectronics for Medical Devices and Systems, J. A. Rogers, R. Ghaffari, D.-H. Kim, Eds.
(Microsystems and Nanosystems, Springer International Publishing, 2016), pp. 173–191.
27. J. C. Case, E. L. White, R. K. Kramer, Sensor enabled closed-loop bending control of soft
beams. Smart Mater. Struct. 25, 045018 (2016).
28. L.-H. Chen, B. Cera, E. L. Zhu, R. Edmunds, F. Rice, A. Bronars, E. Tang, S. R. Malekshahi,
O. Romero, A. K. Agogino, A. M. Agogino, Inclined surface locomotion strategies forspherical tensegrity robots. arXiv:1708.08150 (2017).
29. A. P. Sabelhaus, J. Bruce, K. Caluwaerts, P. Manovi, R. F. Firoozi, S. Dobi, A. M. Agogino,
V. SunSpiral, System design and locomotion of superball, an untethered tensegrity robot,
in 2015 IEEE International Conference on Robotics and Automation (ICRA) (IEEE, 2015),
pp. 2867–2873.
30. Y. Zheng, J. B. Morrell, A vibrotactile feedback approach to posture guidance, in2010 IEEE Haptics Symposium (IEEE, 2010), pp. 351–358.

OmniSkins: Robotic skins that turn inanimate objects into multifunctional robots
Joran W. Booth, Dylan Shah, Jennifer C. Case, Edward L. White, Michelle C. Yuen, Olivier Cyr-Choiniere and Rebecca
Kramer-Bottiglio

Sci. Robotics 3, eaat1853.
DOI: 10.1126/scirobotics.aat1853

http://robotics.sciencemag.org/content/3/22/eaat1853

SUPPLEMENTARY
MATERIALS

http://robotics.sciencemag.org/content/suppl/2018/09/17/3.22.eaat1853.DC1

REFERENCES

This article cites 25 articles, 1 of which you can access for free
http://robotics.sciencemag.org/content/3/22/eaat1853#BIBL

PERMISSIONS

http://www.sciencemag.org/help/reprints-and-permissions

Use of this article is subject to the Terms of Service
Science Robotics (ISSN 2470-9476) is published by the American Association for the Advancement of Science, 1200
New York Avenue NW, Washington, DC 20005. 2017 © The Authors, some rights reserved; exclusive licensee
American Association for the Advancement of Science. No claim to original U.S. Government Works. The title
Science Robotics is a registered trademark of AAAS.

Downloaded from http://robotics.sciencemag.org/ by guest on September 20, 2018

ARTICLE TOOLS