S c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l e
SOFT ROBOTS

Stretchable Arduinos embedded in soft robots
Stephanie J. Woodman, Dylan S. Shah, Melanie Landesberg,
Anjali Agrawala, Rebecca Kramer-­Bottiglio*

INTRODUCTION

Arduinos and other single-­board microcrontrollers are reprogrammable, widely used, and have an open-­source community comprisingmore than 1 million users (1), making their prevalence as controllers
unparalleled in and out of the robotics world. Most soft robots today
are controlled by Arduino-­style microcontrollers (2–6). The modulus
mismatch between rigid Arduino boards and the materials used insoft robots (for example, silicone elastomers) leads many designers toeither place the electronics in regions of the robot designed to experience minimal strain (3) or off-­board them entirely (7–9). Proposedsolutions to this problem include mechanical computing platforms,
soft logic gates, and stretchable electronics.
Instead of relying on conventional electronics, researchers haveproposed fully soft mechanical computing platforms that exploit high-­
dimensional dynamic phenomena to perform computation and act as
distributed information processing networks (10). Most of these non–von Neumann computational architectures take the form of tunablemechanical metamaterials that switch between two discrete states,
analogous to binary digits (bits) in electronic computers. Soft logic
gates have been proposed on the basis of fluidic principles [pneumatic(11, 12) and liquid (13, 14)], pointing toward fully autonomous open-­loop behaviors such as locomotion and arm motion. However, thesemechanical approaches lack the logic gate density to match the capabilities of traditional electronic computers, which have proliferated
because of miniaturization and scaling.
Another approach toward embedded computation in soft robots
is the field of stretchable electronics, where researchers aim to endow traditional computing platforms with stretchability. This approachretains the computational power density of traditional circuitry while
introducing stretchable conductive traces and substrates that linksilicon-­based rigid integrated circuits (ICs). Stretchable traces madefrom geometric patterning of solid thin-­film conductors (for example, serpentines or meshes) are known for excellent interfacing with
Department of Mechanical Engineering and Materials Science, Yale University, 9Hillhouse Ave., New Haven, CT 06511, USA.
*Corresponding author. Email: rebecca.​kramer@​yale.​edu
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11 September 2024

rigid microelectronics (15–18) but typically cannot reach the strainsrequired for soft robot applications (20 to 1000% strain) (19). In
contrast, stretchable traces made from liquid metals (LMs) (20, 21),
LM composites (22–24), or conductive elastomers (25, 26) can often
reach higher strains but, first, have difficulty interfacing with rigid
IC components and, second, display strain-­dependent electrical resistances.
Regarding the former, recent attempts have used acidic or alkaline solutions to improve the electrical conductivity of the IC-­LM
interface (27, 28). Tang et al. (29) presented an LM-­adhesive mixture
to promote substrate adhesion and IC interfacing, yet the inclusion ofadhesive greatly reduced the formulation’s conductance. Other works
highlight how the interfaces between LM-­based conductive inksand commercial ICs often suffer when strained, thus confining examples to low-­strain demonstrations (27, 29–36) or simplified
designs (27, 28, 33, 37). For example, Valentine et al. (38) proposeda non–commercial form, single-­layer, microcontroller circuit but
characterized only a simpler light-­emitting diode (LED) circuit with
LM interconnects under strain.
Regarding the latter, biphasic (solid-­liquid) gallium-­based formulations have been proposed as strain-­insensitive conductors.
Most biphasic metal formulations are made from a mixture of liquid
eutectic gallium-­indium (EGaIn) and solid metal particles [such as
silver (31, 39, 40), copper (41), and nickel (42)] and yield favorable
rheological properties for patterning, interfacing, and enhanced
electrical performance. Formulations with added or natively formed
semiconductive particles such as quartz (43), graphene oxide (44),and gallium oxide (37, 45) boast a suppressed strain response, anespecially promising attribute for stretchable circuitry. We previously
used biphasic gallium-­indium (BGaIn), made from EGaIn within situ formed crystalline gallium oxide (Ga2O3) growth (∼34 wt %of solid), to achieve high conductivity (2.06 × 106 S/m), extreme
stretchability (up to 1000%), suppressed resistance changes whenstrained, cyclic stability (consistent performance over 1500 cycles),and a reliable interface with rigid electronics (37). However, thisprevious biphasic metal formulation was found to be laborious to
produce at scale.
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To achieve real-­world functionality, robots must have the ability to carry out decision-­making computations. However, soft robots stretch and therefore need a solution other than rigid computers. Examples of embedding computing capacity into soft robots currently include appending rigid printed circuit boards to the robot, integrating
soft logic gates, and exploiting material responses for material-­embedded computation. Although promising,these approaches introduce limitations such as rigidity, tethers, or low logic gate density. The field of stretchable
electronics has sought to solve these challenges, but a complete pipeline for direct integration of single-­board
computers, microcontrollers, and other complex circuitry into soft robots has remained elusive. We present a generalized method to translate any complex two-­layer circuit into a soft, stretchable form. This enabled the creationof stretchable single-­board microcontrollers (including Arduinos) and other commercial circuits (including SparkFun circuits), without design simplifications. As demonstrations of the method’s utility, we embedded highly
stretchable (>300% strain) Arduino Pro Minis into the bodies of multiple soft robots. This makes use of otherwise
inert structural material, fulfilling the promise of the stretchable electronic field to integrate state-­of-­the-­art computational power into robust, stretchable systems during active use.

Copyright © 2024 The
Authors, some rights
reserved; exclusive
licensee American
Association for the
Advancement of
Science. No claim to
original U.S.
Government WorksS c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l e
In this work, we present material and interfacial processing solutions to previous challenges that enable a generalized end-­to-­end
method for translating any two-­layer circuit (such as an Arduino)
into a soft stretchable form ready for integration into soft robots andwearable electronics (Fig. 1 and Movie 1). This method is made possible by, first, a scalable stretchable conductor with a suppressedstrain response, cyclic stability, and reliable interfacing to ICs and,second, derived guidelines for conductor-­substrate compatibility,
which determines the reliability of the process. To demonstrate theutility of this method, we translated several open-­source circuit designs containing ICs with dozens of interfaces and vertical interconnect accesses (VIAs) into stretchable forms and characterized theirfunction during high-­strain cycling. We created a soft, stretchable
Arduino Pro Mini that could be stretched to >300% strain and maintain functionality for more than 120 cycles to 100% strain, despite
having more than 70 interfaces between rigid and soft components
and more than 40 VIAs. We further demonstrated the generality ofthe method by fabricating stretchable versions of the Arduino Lilypad,
SparkFun Sound Detector, and SparkFun RGB (Red Green Blue)and Gesture Sensor. Notably, the circuits used the same form factor
and IC packages as the originals, including both no-­lead (for example, dual flat no-­lead) and lead (for example, thin quad flat pack)packages. Last, we embedded stretchable Arduino Pro Minis into thebodies of soft robots at specifically high-­strain locations and used

Choose your circuit

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Reshape for your application

Use in commercial form factor

1 cm

Stretchable tapes

Example: Wearable Electronics

Example: Embedded Electronics in Soft Robots

Fig. 1. End-­to-­end method for translating complex commercial circuit boards into stretchable forms. The method is enabled by biphasic conductors and tackified
silicones, enabling circuit integration into fully functioning wearables and soft robots during use.
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S c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l ethem for embedded computation. The demonstrations collectively
mark a transition from one-­off, functionally limited showcases to robust, reliable, and complex multilayer stretchable circuits.
RESULTS

Scalable, stretchable conductor with suppressedstrain response
Recently, there has been much interest in so-­called strain-­insensitive
stretchable conductors, which have a suppressed strain response
relative to bulk conductor assumptions. In contrast, most traditional
circuits use annealed copper traces (resistivity, 1.72 × 10−8 ohm·m;
density, 8.93 g/cm3; at 20°C). As a classical constant-conductivity
bulk conductor, copper theoretically follows Pouillet’s law (46)when strained
R ∕ R0 = (1 + ϵ)1+2ν

(1)where R/R0 is the relative (normalized) resistance change, ϵ is theapplied strain, and ν is Poisson’s ratio, which is most often assumed
to be 0.5, implying that the conductor is incompressible (37). Although Pouillet’s law predicts large increases in resistance even atmoderate strains for bulk conductors, by engineering materials withstable conductance under large strains, stretchable complex circuits
and low-­loss power transmission can be achieved. Our previous
work presented one such conductor with an electromechanical response
suppressed far below that predicted by Pouillet’s law—a BGaIn composition formed from semiconductive crystalline gallium oxide
particles mixed with EGaIn (37, 45). However, BGaIn is labor intensive to produce, and the synthesis process yields small quantities
per batch.
Another proposed biphasic conductor is oxidized gallium-­indium(OGaIn) (47, 48), a biphasic foam containing amorphous gallium
oxide particles and EGaIn. OGaIn is made via rigorous mixing of
EGaIn in air and can be created at scale. In this study, we sought torigorously characterize OGaIn in an attempt to replicate the desirable properties of BGaIn with a material that can be manufactured ata scale useful to industry. Despite the OGaIn and BGaIn materials
having similar qualitative rheological characteristics, we measured
OGaIn to be only 1.4 wt % of amorphous gallium oxide [close to the
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Deriving guidelines for conductor-­substrate compatibility
The wetting and adhesion of LMs and biphasic metals to a host substrate are important parameters in stretchable electronic applications (55, 56). In this work, we relied on the adhesion of OGaIn toboth its underlying substrate and its colocated ICs. Given the cyclicstability shown in Fig. 2 (B and C), we inferred that this adhesion is
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Movie 1. Stretchable Arduinos overview. Using a biphasic (solid-­liquid) EGaIn-­
based conductor, we created stretchable versions of several popular open-­sourced
circuits, including the Arduino Pro Mini. In this video, we show testing of the circuits and then embedding them into soft robotic systems to aid in sensing andcontrol.

1.21 wt % reported by Chen et al. (49)], whereas BGaIn was ∼34 wt% of solid crystalline gallium oxide (37). We surmised that OGaIn is
primarily thickened through air inclusions (48), which are not accounted for in the weight percent of formulations. The density of
OGaIn (4.65 g/cm3 at 20°C) was substantially lower than EGaIn’s(>6 g/cm3). Scanning electron microscope (SEM) micrographs,
energy-­dispersive x-­ray spectroscopy (EDS), and x-­ray diffraction
analysis (fig. S1 and Supplementary Methods) suggested that thehardness of the gallium oxide that forms at the OGaIn-­air interface
prevents deformation of the air inclusions upon stretching, which
could explain the observed viscosity enhancement of OGaIn relative
to neat EGaIn. We further investigated the rheological properties of
OGaIn, revealing its shear-­thinning behavior, which suggests compatibility with extrusion printing techniques (fig. S2). Last, OGaIn and
BGaIn exhibited similar bulk electrical conductivities of 2.11 × 106 and2.06 × 106 S/m (37), respectively.
To assess the electromechanical performance, we patterned 250-­μm
traces of OGaIn (as wide as the thinnest trace in the commerciallyavailable Arduino Pro Mini; see Materials and Methods and fig. S3A)
onto an ASTM (American Society for Testing and Materials) D412
(50) standard dog-­bone shape of acrylic foam tape [VHB (very highbond) tape, 3 M] that adheres strongly to IC packaging (fig. S3, B andC) and encapsulated the traces with rubber cement (Elmers Inc.).
We then strained each sample to 400% strain (limited by our test
setup). We found that the electromechanical response of OGaIn
was below that predicted by bulk-­conductor assumptions (Pouillet’slaw; Fig. 2A) (37, 46, 51). As one point of comparison, OGaIn had
an R/R0 of 7 at 400% strain compared with 25 for a bulk conductor.
Further, the R/R0 versus ϵ behavior of OGaIn matched previously
reported values for BGaIn in the range where comparison was possible (up to 100% strain) (45). To provide a more direct comparison, we additionally tested OGaIn and BGaIn on the same substrate
and with the same trace width (fig. S4), finding similar agreement.
OGaIn is thus a scalable replacement for BGaIn. To evaluate cyclicstability, we subjected single-­trace samples [unstretched resistanceof ∼0.5 ohm, which is consistent with previous literature (52, 53)]
to 1000 cycles of 150% strain at 15 mm/min (Fig. 2B).
After an initial break-­in period of a few cycles (54), the trace resistance increased by only ∼0.5 ohm between cycles 5 and 1000. To
evaluate the interfacing stability between traces and rigid IC contact
pads, we repeated the cyclic strain (Fig. 2C and fig. S3E) and highstrain (fig. S5) tests with two traces bridged by a 0-­ohm resistor(Digi-­Key Inc.). There were no discernible differences between theinterfaced and noninterfaced traces whether comparing the initial
raw resistance or the resistance after cycling. This, along with contact resistance measurements (fig. S6), indicates that the slight increases in resistance observed with cycles are not attributable tointerfacing. Possible sources of increased resistance may include anelongation of the trace length after stretching (because of viscoelastic properties and plastic deformation of the surrounding polymers)
or a change in OGaIn’s effective electrical conductivity (for example,
through phase separation).

S c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l ewith a tack value of at least 0.18 N to ensure sufficient OGaIn-­substrateadhesion, stable IC placement, and general conductor-­substrate compatibility for stretchable circuits.

Woodman et al., Sci. Robot. 9, eadn6844 (2024)

RR((Ω))oGaIn
Adhesion
OGaIn
Adhesion (N)(N)

R (Ω)

R/R0

Translating complex circuits into stretchable forms
Having identified a suitable stretchable conductor and generalized
its compatibility with soft, stretchable substrates, we then developed
a method of translating the as-­is, complex circuit-­board designs into
stretchable circuits. Throughout the development of the method reported herein, we emphasized accessibility, aiming to eliminate aneed for extensive equipment or materials expertise or circuit design expertise. We applied the method to make stretchable versionsof the popular Arduino Pro Mini, a reprogrammable single-­board
microcontroller, as well as the Arduino Lilypad, SparkFun Sound
Detector, and SparkFun RGB and Gesture Sensor.
The circuits were fabricated using laser cutting and stencil printing(Fig. 3). The substrate (for example, VHB tape) was sandwiched between
two layers of 0.1-­mm-­thick sticker paper that acted as a mask. The main
trade-­off we noted in selecting the sticker paper was that thinner paper
allowed for more precise traces, whereas thicker paper facilitated easierremoval and reduced smearing of traces because of ripping. The board
outline and VIAs were cut using a carbon dioxide (CO2) laser (Universal
Laser VSL 2.30DT), and the trace outlines were etched on the bottom maskusing an ultraviolet (UV) laser (LPKF
A
B
2
Protolaser U4). OGaIn was painted onto
BGaIn
Pouillet’s Law
OGaIn
25
25
the bottom traces, the mask was removed,
2.5 OGaIn
and the circuit was encapsulated with a thin
BGaIn
1.5
1.5
20
20
layer of rubber cement (Elmers Inc.). Next,
Pouillet's law
the top traces were made using the same
0
15
0
15
laser and painting procedure, followed by80
1component placement and a rubber cement
10
10
sealing step. Last, silicone adhesive (Sil-­2
Poxy, SmoothOn Inc.) was added to a small
0.5
0.5
5
region around the microprocessor to reducestress caused by the stiffness gradient. For
0.5
200
205
00
full process details, we refer the reader to
0
0
100
200
400
300
0
1000
500
0
100
200
300
400
0
500
1000
Materials and Methods. In contrast with our
Cycle Number
Strain (%)
more restrictive prior art that used transfer
printing (37), this scalable screen-­printing–CD
2
2and laser cutting–based process enables the
0.25
0.25
creation of encapsulated multilayer circuits using substrates that meet the compatibility
1.5
1.5
requirement (tack ≥ ∼0.18 N) and can accommodate dense IC components while
0.2
0.2
withstanding high strains. Furthermore, in11
creased adhesion led to increased robustness of the IC-­OGaIn interfaces, allowing us
2
0 Ω Resistor
0.15
0.15
to directly transfer commercial circuits into
0.5
0.5
stretchable forms.
Straining the soft Arduino Pro Minis
0.5
200
205
to failure (defined as a disconnection of
0.1
0
0.1
1000
500
10
0
00
500
1000
0
55
10
serial communication to the computer;
Tack (N)Cycle Number
see Materials and Methods, Fig. 4, A to C,
Tack (N)and movie S1; strain rate, 15 mm/min),Fig. 2. OGaIn characterization and substrate compatibility. (A) Normalized resistance change versus strain for five
we found that serial disconnect always
OGaIn samples, plotted alongside the theoretical values for a bulk conductor and previous results from our BGaIn
alloy (45). Shaded regions represent one SD. (B) Representative electrical resistance versus cycle number for an OGaIn occurred because of loss of electrical contrace stretched to 150% strain over 1000 cycles. (C) Representative electrical resistance versus cycle number for an tact or shorting of the traces before meOGaIn trace with a 0-­ohm resistor stretched to 150% strain over 1000 cycles. (D) OGaIn adhesion versus ASTM D6195-­22 chanical failure of the substrate. The averagestrain at serial disconnect was 328%, withtack measurement of various stretchable substrates. Error bars indicate one SD from the mean over five trials.
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sufficient with the VHB tape. However, toward our goal of embedding complex stretchable circuits into the bodies of soft robots, wesought to characterize the adhesion of OGaIn to other materials commonly used in soft robotics, in addition to probing how to modify existing materials to improve adhesion. Further, we selected substratematerials to derive a generalized correlation between OGaIn-­substrateadhesion and substrate material tack.
We compared a baseline VHB tape substrate with four silicone
elastomer (Dragon Skin 10, abbreviated as DS10, SmoothOn Inc.)
substrates with increasing fractions of a tactile mutator (Slacker,
SmoothOn Inc.). We refer to the neat silicone elastomer as DS10,
the formulation with a mixing ratio of 1:1:1 (part A:Slacker:part B)
as Slacker 1, and formulations with mixing ratios (1:1.5:1) and (1:2:1)
as Slacker 1.5 and Slacker 2, respectively. Further details can befound in Materials and Methods.
Our tests show a positive linear correlation (R2 = 0.96) between
substrate tack and OGaIn-­substrate adhesion (Fig. 2D). All substrates had at least some OGaIn adhesion, even with <0.1-­N tack,which is likely due to the oxide particle inclusions in OGaIn (55)that encourage wetting (56). In practice, we found that substrates
with low tack values (such as neat DS10 and Slacker 1 in Fig. 2D)
increased the likelihood of failure modes (such as trace defects andIC shifting; table S1). Therefore, we recommend selecting substrates

S c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l eABPaint OGaIn andfill VIAs (bottom)

I

Remove bottom maskoGaIn

Circuit substrate

E

Laser cut VIAs

Laser cut top
circuit pattern

Laser cut bottom
circuit pattern

CO2 laser

UV laserUV laserJ

Encapsulate bottom
Encapsulant

F

K

Repeat G-I for top
pattern

L

Place ICs and wires
IC components

Encapsulate top
and add Sil-PoxyFig. 3. Circuit manufacturing. (A) Original, open-­source Arduino Pro Mini file in Autodesk Eagle. (B) Modified circuit design ready for laser cutting. (C) Circuit substrate
sandwiched between sticker paper. (D) Laser cut board outline and VIAs in sticker paper with CO2 laser. (E) Cut top layer of circuit traces using UV laser. (F) Cut bottom
layer of circuit traces using UV laser. (G) Paint bottom traces and fill VIAs with OGaIn. (H) Remove bottom mask and test trace conductivity. (I) Encapsulate with material of
choice. (J) Paint top traces with OGaIn and remove mask. Test trace conductivity. (K) Place components and wires. (L) Encapsulate top. Add Sil-­Poxy around microprocessor.

the five samples failing between the range of 202% strain and 404%
strain, corresponding to a failure in the plastic regime of each force-­
displacement curve (Fig. 4D). For two of the five samples tested, thecircuit no longer functioned after returning to the unstrained state.
However, two samples rebooted in an error state (no serial communication), and one sample remained reprogrammable after beingstrained past initial serial disconnect.
Cycling the Arduinos to 100% strain (rate of 15 mm/min) demonstrated stability over at least 100 cycles, with the average numberof cycles at failure being 124 and one sample reaching 200 cycles
before failure (Fig. 4E). For cyclic testing, circuits would be functional until an initial failure and not recover after that first failure
even when unstrained. Force versus strain curves for neat substrates(VHB) and circuit-­embedded substrates reveal that the circuits havea slight bulk stiffening effect on their host materials, although thisappears to diminish with further cycling (Fig. 4F). After 200 cycles,
the materials exhibited similar behavior, with the force at 100%
strain only 27% higher for the circuit compared with neat VHB. Bothcycles exhibited similar plastic deformation after the first cycle (theMullins effect) (57).
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Posttest analysis revealed that the strain-­limiting Sil-­Poxy region
around the microprocessor, although it prevented shorting between
microprocessor pins, introduced the most common failure mode of
trace bridging at the edge of the strain-­limiting region (fig. S7). This
result suggests that the soft circuits could be improved by introducing stiffness gradients into the substrate (58). Another failure mode
observed was at the trace-­IC interface, indicating that enhancing theinterfacial electrical connections could extend the operational strain
range of the circuits. In addition, two trace failures were observed
during cyclic testing, seemingly unrelated to a rigid-­soft interface.
These failures are suspected to be caused by trace thinning becauseof viscoelastic effects.
To ensure generality with respect to commercial circuit design
and IC package types, we stretched to failure one sample each of theArduino Lilypad, SparkFun Sound Detector, and SparkFun RGB
and Gesture Sensor (Fig. 5 and movie S2). The Lilypad, whose
rigid counterpart was specifically intended for wearable applications, strained to 415% before slipping out of its mount while still
functioning (Fig. 5A). The Sound Detector, which is an analog circuit containing a through-­hole mounted microphone, strained to a
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H

D

Sticker paper

Modify for design
constraints

Original pattern

GCS c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l eACircuit SchematicB

C

Circuit (top view)

Instron Pull-to-Failure Example

VIA

VHB substrate

0% Strain404% Strain

Top OGaIn trace
Microcontroller
Bottom OGaIn trace

3

E

F

Serial Disconnect - Avg 328%

Serial Disconnect - Avg 124
5

1

0
0

Connected Disconnected
300
400
100
200
Strain (%)

1.5

4

Force (N)Sample Number

Force (N)

2

2

3
2

1
Cycles

0.5

1

1
0

50

100
Cycles

150

200

0

10 200Circuit
Neat VHB
050
Strain (%)

100

Fig. 4. Circuit characterization. All circuits in this figure used VHB tape as a substrate. (A) Circuit schematic showing top and bottom traces in red and cyan, respectively,
and VIAs in black. (B) Identifying key circuit components and materials. Note that the top and bottom interconnect layers can be seen because VHB tape is translucent. In
addition, the VIAs can be seen as round dots at various locations on the interconnects. Scale bar, 5 mm. Trace widths in insets are 0.25 mm. (C) Image of circuit before strain
testing on the materials testing system (Instron 3345) and just before serial disconnect at 404% strain. Scale bars, 18.8 mm. (D) Force versus strain curves for each sample
when strained until serial disconnect, noting when serial disconnect occurred for each sample. (E) Cycle number when serial disconnect occurred for each sample, when
the circuit was repeatedly strained to 100%. (F) Comparing cyclic behavior of neat VHB tape (circuit substrate material) and the circuit at 1, 10, and 200 cycles. Solid lines
are means over five samples after the number of strain cycles indicated in the legend. Shaded area indicates one SD.

lower strain of 258% (Fig. 5B). Last, the RGB and Gesture Sensor
only uses no-­lead IC packages, endowing it with higher stretchability, and it strained to 442% without failure (Fig. 5C).
Soft robots with embedded soft computers
The soft Arduino Pro Minis were embedded into three soft robotic
systems where, first, an Arduino controlled the gait of a locomotive
robot; second, an Arduino sensed and communicated physical contact between agents in a multirobot system; and, third, an Arduino
categorized the stretch data (low, medium, and high) and visuallyindicated the user’s motion in a wearable system (Fig. 6).
Onboard pneumatic control of a quadruped soft robot
We first aimed to demonstrate how soft single-­board microcontrollers,and by extension other complex circuits, can be embedded into
the structural material or unused surface area of soft robots—even at
high-­strain locations. We fabricated stretchable Arduino circuits on,
first, a silicone substrate (Slacker 1.5) (Fig. 6A), which matches
the material of a silicone robot, and, second, a VHB tape substrate
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(Fig. 6B) and integrated them into a canonical quadrupedal soft robot form factor (see Materials and Methods) (3, 8). In both cases,
the microprocessor IC was integrated into the robot at the locationof the highest strain during robot locomotion. The onboard soft Arduino was powered by a USB (universal serial bus) cable and used
an I2C (interintegrated circuit) to command off-­board pressure regulators (59) to inflate the actuators and generate a forward walking
gait (Fig. 6C). The soft Arduino achieved successful processing andexternal communication at maximum strains of ∼100% (movies S3and S4). The soft Arduinos featured a custom layout in this demonstration, while keeping the most delicate components in the area ofhighest strain, to showcase that design modifications can be made to
tailor-­fit the host robot (Fig. 1).
Neighbor-­neighbor sensing in a multiagent system
To illustrate scenarios where embedded computation could enable
new capabilities in mobile soft robots, we integrated soft Arduinos
into the surface of fully stretchable, pneumatic VoxelBots (60, 61).
Notably, the VoxelBots contain no strain-­limiting surfaces, precluding
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Wires

D

S c i e n c e R o b o t i c s | R e s e a r c h Ar t i c l erigid onboard printed circuit boards (PCBs) and requiring all included circuitry to be stretchable. This multiagent demonstration isa step toward our vision of a cell-­like, modular approach to distributed computation, wherein robot modules may reconfigure relative
to one another as a form of global shape change (62).
The VoxelBots were created by casting hollow cubes of silicone(DS10), bonding them together using silicone, inserting pneumatic
tubing, and attaching stretchable VHB-­based Arduinos using DS10
(see Materials and Methods). To implement a visual output, we additionally added a stretchable LED board (fig. S8) connected to theArduino (Fig. 6D) embedded into the surface of the VoxelBot. Last, toallow each VoxelBot to sense contact with other VoxelBots, one of theA415%

B 258%

C 442%DISCUSSION

Fig. 5. Additional circuits. (A) Arduino Lilypad in rigid and soft form at 0% strain
and the soft form at 415% strain. Scale bars, 7 mm. (B) SparkFun Sound Detector in
rigid and soft form at 0% strain and the soft form at 258% strain. Scale bars, 9 mm.
(C) SparkFun RGB and Gesture Sensor in rigid and soft form at 0% strain and thesoft form at 442% strain. Scale bars, 9 mm.

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We presented a generalized, scalable, accessible, end-­to-­end method
to translate complex two-­layer circuits into soft, stretchable forms.
We used and characterized a biphasic stretchable conductor with asuppressed strain response, cyclic stability, and robust interfacing
to ICs and determined that substrates with a tack of ≥0.18 N arenecessary for conductor-­substrate compatibility. These revelations
together allowed us to introduce a commercial-­form stretchable Arduino. We further made stretchable forms of other commercial circuits, from the popular vendors Arduino and SparkFun, that show
the breadth and generality of the method to a wide range of open-­source, commercially available designs.
We integrated stretchable Arduino Pro Minis into several soft
robotic systems in locations where they experienced >100% strain.
These integrations demonstrated soft locomotion quadrupeds withembedded electronics to control gait, a fully soft two-­agent robotic system using onboard, stretchable control and sensing, anddetection of a user’s arm motion in a smart garment with the stretchable circuit intentionally placed in the area of the highest strain. The
simplicity, accessibility, and success of the stretchable circuit fabrication method described herein give it the potential to be widely adopted by researchers, hobbyists, and those in industry. All of ourcircuits are based on open-­source designs, and our design files used
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Arduino’s analog pins was connected to an exposed OGaIn trace on
one of two front faces on the robot. The other face, on the bottom,
contained an exposed OGaIn trace connected to the Arduino’s ground(GND) pin. The completed VoxelBots were then sequentially inflated
and deflated using compressed air to locomote toward each other overapproximately 30 steps (Fig. 6E), and the onboard soft Arduino wasprogrammed to sense and report contact with the other VoxelBots.
When the input pin (A3) and GND pins on each robot made contact,
their embedded Arduinos detected the voltage change and lit the VoxelBots’ green LED to indicate successful contact (Fig. 6F and movie S5).
Colocated computation and sensing in a wearable system
Given that the maximum strain of the stretchable Arduinos (on average, 300%) far exceeds the maximum strain experienced by the human body (∼75% strain) (63), they can be placed nearly anywhereon smart garments. In contrast with previous works that use stretchable conductors as strain sensors and locate the IC interfaces in low-­or no-­strain locations (29, 36, 38, 64), we intentionally placed oursoft Arduino on the high-­strain elbow skin (Fig. 6G). We pressed a
VHB-­based Arduino and accompanying LED board (fig. S8) onto a
Spandex elbow sleeve (using the VHB tape and rubber cement’s natural adhesion) with an embedded textile capacitive strain sensor(Fig. 6G) (65). Red, yellow, and green LEDs were attached to threepins of the stretchable Arduino (see Materials and Methods).
The Arduino was programmed to convert voltages from the sensing board to capacitance and print capacitance values to the serial
port. Simultaneously, the Arduino indicated the strain range by lighting up the green, yellow, or red LEDs (Fig. 6H and movie S6). The red
LED indicated a high strain (>80 pF), yellow indicated a middle
range (78 to 80 pF), and green indicated little or no strain (<78 pF).
Capacitance increases with strain because of an increase in surface
area of the parallel plate electrodes (65). Overall, this demonstration
highlights the design freedom enabled by high-­strain interfaces withrespect to circuit placement.

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Embedded soft Arduino controls robot

AC

I2C Communication

I2C Breakout
Board

t=0s

USB for Power
& 2-way Serial
Communication

Compressed
Air Supply

Pressureregulating
Solenoid Valves

Air Supply to Robot Actuators

Air SupplyLEDs

t = 111 s

USB for Power &2-way Serial
Communication

Downloaded from https://www.science.org at Yale University on September 11, 2024

Encapsulated VHB
ArduinoExposed OGaIn
Trace

Soft, multi-agent contact sensing

VHB Circuit on DS10 Robot

100% peak strain

DF

A3 PinGND
DS10 Robot

Soft agents locomote toward each other and sense contact

E

Deflated - 0% strain

G
Wearable Arduino visualizes sensor data

B

DS10 Circuit on DS10 Robot

Inflated = ~30% strain
SpandexCompression Sleeve

ShoulderH

Sensor
Processing
Board

Stretchable Fabric
Strain Sensor

SerialConnection/Data
CaptureVHB Arduino
and LED
Board
Wrist

Fig. 6. Embedded computation in soft systems. (A) Silicone circuit embedded in a silicone (DS10) robot before it takes a step and mid-­step, in a location where thecircuit experiences ∼100% strain. (B) A circuit with VHB as the substrate is mated to a DS10 robot at full inflation and at different times during the walking gait. Scale bars,
8 mm. (C) Schematic of the quadruped driven by its embedded Arduino. (D) Stretchable Arduinos used for contact sensing in a two-­robot system. (E) Top view of the robot
before and after inflation (before taking a step and mid-­step). Scale bars, 8 mm. (F) Robots’ initial poses and after they make contact. Scale bars, 10 mm. (G) Stretchable
Arduinos integrated with sensing circuitry in a smart garment that senses the user’s elbow bending motions. (H) Sequential images showing a user bending their elbow
and the Arduino detecting the motion as displayed by the gauge. Scale bars, 7 mm.

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MATERIALS AND METHODS

OGaIn fabrication and characterization
OGaIn was fabricated by measuring 200 ml of EGaIn into a 250-­ml
glass beaker and mixing using an IKA Eurostar 20 digital mixer, witha four-­blade stainless steel propeller, for 30 min (fig. S3A). Resistivity and conductivity were estimated by measuring the resistance of a
trace with known length, width, and height using a four-­point probe
multimeter (B&K Precision). The weight percent of solid particles
was measured by weighing a sample of OGaIn before and after dissolving the solid particles in 12 M HCl.
The density was measured by weighing a known volume of OGaIn.
A 2.54 cm–by–2.54 cm–by–0.64 cm mold was precision-­cut fromacrylic using a laser and then securely clamped to another acrylic
piece. The weight of the empty mold was recorded. OGaIn was
carefully applied into the mold using a wooden craft stick, ensuring
thorough filling of corners and the absence of air gaps. Excess material was removed by drawing the craft stick across the mold’s top.
The filled mold was weighed again, and the OGaIn density was calculated by subtracting the empty mold weight from the filled moldweight and dividing by the known volume. We measured the density of three samples and reported the mean.
X-­ray diffraction testing was completed on a Rigaku SmartLab
machine with a 2-­mm window. SEM images were taken on a Hitachi
CFE SU8230. EDS analysis was performed with a Bruker QUANTAX FlatQUAD (mapping at 5 kV and compositional analysis at 6 kV).
Surface samples were prepared on 12.5-­mm stubs on carbon tape.
Cross-­sectional samples were prepared on vertical sample holders
on carbon tape, where a trace of OGaIn was frozen and then broken in half and mounted to the stub. Stretched cross sections were
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prepared by casting OGaIn on VHB, encapsulating with rubber cement, and then stretching the substrate while applying to the SEM
stub. After mounting the sample, it was frozen and then broken toreveal the stretched cross section.
The single-­trace samples were created using the dimensions andelectrode attachment techniques described in (45), with VHB tapeand rubber cement as the substrate and encapsulant, respectively.
The trace widths of OGaIn were 250 μm, with a gauge length of 25 mm(fig. S3, B and C). Resistor samples of 0 ohm were made using thesame patterns and processes but with a 0.25-­mm gap in the middleof the trace, over which a 0402 0-­ohm surface-­mount resistor wasplaced (fig. S3E). The single-­trace samples were characterized using
the custom setup previously described in (45) and illustrated in
fig. S3D. An Arduino-­driven lead-­screw actuator controlled the strain
and strain rate, and resistance was recorded using a four-­point probe
multimeter (B&K Precision).
Substrate viability characterization
ASTM D6195-­22 standard tack testing was carried out using an Instron 3345 tensile tester (maximum capture rate, 2 ms; fig. S9A).
Five samples of each material were created as follows: VHB tape wasadhered to the polyethylene terephthalate backing, ensuring that no
air bubbles were present. The DS10 (Dragon Skin 10A, SmoothOn
Inc.) samples were made by casting DS10 over the polyethylene terephthalate backing with a 0.5-­mm draw bar. That same technique
was used to create the samples of Slacker 1, Slacker 2, and Slacker 3.
Slacker 1 used one part DS10 part B, one part Slacker (SmoothOn
Inc.), and one part DS10 part A (denoted 100:100:100). Slacker 1.5
used the ratio 100:150:100, and Slacker 2 used 100:200:100.
The same setup, sample creation, and procedure were used for
the OGaIn adhesion as for the previously described tack testing, although, instead of coming into contact with steel, the samples cameinto contact with molded OGaIn (fig. S9, B to E). A 25 mm–by–
25 mm–by–1.59 mm–deep mold was created to fit onto the steel bar
used for previous experiments (fig. S9B). This mold was filled with
OGaIn before each new sample, and a bar was drawn across the top
surface before removal of the mold (fig. S9C).
To get an application-­based analysis of the effects of OGaIn-­
substrate adhesion on the circuit manufacturing process, defect rate
tests were carried out. Five traces (250 μm in width and 45 mm inlength) of OGaIn were screen-­printed onto each of the substrates(VHB tape; DS10; Slacker 1, Slacker 2, and Slacker 3) using a sticker
paper mask. The conductivity of each trace was measured, and abinary rating of conductive or nonconductive was recorded for eachtrace (table S1).
Stretchable Arduino Pro Mini manufacturing
The circuit pattern for the Arduino Pro Mini was downloaded from
Arduino.com in the industry-­standard Eagle PCB design file format.
The relevant circuit layers—bottom, top, VIAs, and header pin holes—
were exported to CorelDRAW for postprocessing and to prepare thefiles for laser cutting (Fig. 3A). In CorelDRAW, GND lines were added
to replace the commercial PCB’s GND pour. VIAs and header pin holesizes were reduced to 0.4 mm in diameter (Fig. 3B). The reduction in
VIA size from the open-­source design to the soft design left sufficient
clearance between the VIAs and traces, as well as the header pins andtraces. The implemented circuits also featured a minimum trace
width of 0.2 mm, a minimum clearance between VIAs and traces of
0.29 mm, and a minimum distance between traces of 0.17 mm.
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to create the masks have been made available in our accompanying
GitHub repository.
Our long-­term goal is to develop stretchable versions of a wide
range of familiar circuits (for example, within the Adafruit and SparkFun communities), advancing the field of soft robotics and wearables and lowering the barrier to entry into soft robot research byenabling the use of common control platforms. Important functionalities could be added to make the robots more self-­contained, suchas Bluetooth modules and flexible/stretchable batteries to reduce
external wiring requirements and soft valves to bring additional
pneumatic capabilities onboard. The process could be further tested
to determine Gerber-­like style guidelines, which could then be added
into common design software (such as Eagle or Altium) to determine design viability in stretchable form. In addition, we hope that
this technique will be adopted by vendors of proprietary circuits,alongside an industry-­academia joint effort to develop standardized
connectors analogous to Qwiic (SparkFun Inc.) or USB connections
from rigid electronics.
Future work will include further improving maximum circuit strains,
possibly through increased substrate tack or surface treating the ICs
with adhesion promoters. We also aim to reduce the manufacture
time using commercial stencil-­printing machines for the traces, nozzle dispensing for VIAs (42), and automated pick-­and-­place machines
for the ICs. We hope that this work will enable further research into
soft systems endowed with computational intelligence rivaling today’s
rigid systems without sacrificing compliance, thus facilitating the realization of soft robots that can sense, decide, act, and adapt in thereal world.

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Circuit characterization
The five Arduino Pro Mini samples used for pull-­to-­failure tests
were manufactured with a border on the edges such that fabriccould be adhered, limiting the strain in those regions and ensuringthat only the circuit board was straining. To set up, these fabric regions were gripped (Instron 2713-­007) by the materials testing system (Instron 3345), and the wires for serial connection were plugged
into an FTDI (Future Technology Devices International Limited)
programming board (DEV-­09716, SparkFun), which was connected
to a laptop. A code that flashed four off-­board LEDs and printed
time stamps to the serial monitor was uploaded to the soft Pro Mini.
The laptop and Arduino were recorded by an external camera setup.
The Instron captured force and displacement data while it pulled
upward at a rate of 15 mm/min until serial disconnect occurred. The
initial length and length at failure of the circuit were calculated fromthe camera footage (with one initial frame and one frame just before
serial disconnect), and from these, engineering strains were calculated. This same process was used to test the failure of the three
additional example circuits, one sample each, although they weregripped with acrylic adhered to the circuit as the strain limiter. The
Arduino Lilypad was strained until the LED stopped blinking at
the rate specified in the script. The SparkFun Sound Detector was
strained with loud ambient noise to detect the failure time. The
SparkFun RGB and Gesture Sensor sent color output through serial
until an error reading serial occurred. For all measurements in thispaper, we chose to calculate the strain clamp to clamp (field standard)(17, 26–28, 36).
Cyclic testing of the soft Arduino Pro Minis used the same cyclic
testing device as for the single-­trace samples. The same additional
grip areas were used, but instead of attaching fabric, laser-­cut piecesof 3.18-­mm acrylic were pressed onto either side of the excess VHB
tape such that the four through holes fit onto the alignment pins of
the cyclic tester (fig. S11). The cyclic tester strained to 100% strain
for 1000 cycles, while a time-­lapse camera monitored the laptop
screen, which concurrently displayed the serial output from the soft
circuit and the cycle number from the testing device. The number ofcycles the circuit survived was recorded as the cycle before an error
was seen in the serial output of the stretchable Arduino. After pull tofailure and cyclic testing until serial disconnect, the samples were
evaluated using the two-­point probe FLUKE multimeter to determine where the failure occurred (fig. S7C).
To determine the effect the circuitry had on the circuit substrate’s
force-­strain relationship, the same strain-­limiting fabric pieces wereattached to five stretchable Pro Mini circuits and five pieces of plain
VHB tape. The materials testing system gripped these sections andstrained each sample to 100% strain for 200 cycles at 15 mm/min.
Data from cycles 1, 10 (after Mullin’s effect) (57), and 200, straining
and relaxing, were isolated for each sample. The means and SDs
were then calculated for the five samples from cycles 1, 10, and 200,
straining or relaxing.
Fabrication and design of a quadruped
The soft quadruped robot was inspired by Shepherd et al. (8). The
top portion of the robot was DS10 cast in a three-­dimensional(3D) printed mold. Once cured, this top portion of the robot wasplaced onto fabric impregnated with uncured DS10, and the twoparts cured together, with the bottom fabric acting as a strain-­limiting
layer. The bladders for the four legs and the body each had an exit toopen air that, instead of being on the top, was out the sides. In these
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Here, we detail the manufacturing procedure illustrated in Fig. 3
and recorded in movie S7. Although Fig. 3 presents a general procedure, this text will use VHB tape (VHB 4905, 3M Inc.) as thecircuit substrate and rubber cement (Elmers Inc.) as the encapsulant. If a DS10/Slacker circuit was desired, we replaced the VHB tapewith a cured 0.5-­mm casting of Slacker 1, Slacker 1.5, or Slacker 2
and replaced rubber cement with uncured Slacker 1, Slacker 1.5,
or Slacker 2. To compare each material’s stiffness, we measured
the 100% modulus of all materials used in this manufacturing process following ASTM D412-­16, with dog-­bone type C (fig. S10).
Briefly, the modulus of Sil-­Poxy E sp was about four times thatof DS10 (EDS10), which was similar to those of VHB and rubber
cement, followed by Slacker 1, Slacker 1.5, and Slacker 2 being<0.2 × EDS10.
First, sticker paper from the back of double-­sided tape (Le Papillon Jewelry, Amazon) was adhered to both sides of the VHB tape,and bubbles were removed using a flat edge of a piece of acrylic(Fig. 3C). Then, a CO2 laser (ULS VLS2.30DT) was used to cut theboard outline and the VIAs/header pin holes, using settings of 100%
power and 20% speed, for two repetitions (Fig. 3D). Next, the top
and bottom traces were cut into just the top and bottom pieces ofcircuit paper, respectively, with a UV laser (LPKF ProtoLaser U4,
LPKF Inc.). The CO2 laser, with a beam width of ~300 μm, efficiently cut through the substrate but had relatively low resolution. Conversely, the UV laser, with a beam width of 15 μm, could cut precise,high-­resolution mask traces but was unable to cut through the substrate. To ensure alignment, the board outline was cut into a piece of
paper, and the circuit was then placed into the cutout in the paper
top side up and taped in place. The top traces were then engraved
into the mask (Fig. 3E). After flipping the circuit over its neutral axis
and aligning in the paper cutout, the bottom traces were then engraved (Fig. 3F).
The pieces of sticker paper where the conductive material should
go were removed with tweezers from the bottom side. The VIAs
were filled with OGaIn using a sharp multimeter probe (FLUKE
TP88). Then, OGaIn was painted into the mask using a paintbrush—brushing perpendicular to traces and in circles over them(Fig. 3G). Last, the edge of a piece of acrylic was used to scrape excess material off the top, and the mask was removed (Fig. 3H). Eachtrace was tested for conductivity using a two-­point probe multimeter (FLUKE 83V) with the probes listed previously. For encapsulation, rubber cement was loaded into a syringe and extruded out of a17-­gauge needle over all exposed OGaIn (Fig. 3I).
Once the bottom side was cured, the same process was repeateduntil top mask removal (Fig. 3J), and components were placed exactly as they were on the rigid Pro Mini using tweezers. Wires werethen placed with tweezers and adhered with Sil-­Poxy (SmoothOn
Inc.) (Fig. 3K). Next, a program was uploaded to the device to test
for functionality. Last, the top was encapsulated, and the Sil-­Poxy
was added over the microprocessor and oscillator to create a strain
gradient. Once cured, the circuit was tested again. Notes on improving and scaling this process can be found in Supplementary
Methods.
The same process was used to make the other example circuits(SparkFun Sound Detector, Arduino Lilypad, and SparkFun RGB
and Gesture Sensor), using their open-­source designs. An extremely
fine layer of Sil-­Poxy was added to the bottom layer under the RGB
sensor IC, and no encapsulant or Sil-­Poxy was added directly overthe lens.

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Fabrication and design of voxel robots
The voxel robots were composed of 16 voxels, each with dimensionsof 15 mm by 15 mm by 60 mm, as fabricated and assembled in previous work (60, 61). Sil-­Poxy was used to secure tubes in each bladder and apply friction-­biased acrylic feet (fig. S13) to ensure 1D
motion over the muslin fabric surface.
A stretchable LED array board was manufactured using the same
method as the regular circuitry (fig. S8) and consisted of three LEDs
(red, yellow, and green) and three 220-­ohm resistors. The GNDs allconnected to a point on the board that would be next to the GND
pin on the Arduino when placed side by side. The three lines fromthe LEDs also came to their ends directly across from a set of digitalpins on the Arduino. This board design was used for this demo andthe wearable demo.
The stretchable Arduino and LED board were placed next to eachother on top of each voxel robot, with an ∼1-­mm overlap between
the sensing board and the Arduino so that the two boards would notseparate when strained. Using tweezers to pull up the encapsulant
and sewing scissors to cut it away, a digital pin, two GNDs, and pin
A3 were exposed. Using a multimeter probe, OGaIn was painted
from the digital pin on the Arduino to the LED trace on the breakout
board and from GND to GND. These connections were then encapsulated. Next, the A3 pin was extended in the same manner, painting
a path all the way to the top, front-­facing voxel on the voxel bot, andcovering that face (not encapsulating to maintain conductivity). The
same was done to connect the other GND to the bottom voxel.
The soft Arduinos ran a code that spent half of the time listening
for a 5-­V signal and half of the time sending a 5-­V signal. This way,
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when the A3 and GND pins on each robot made contact with eachother, they would light up the green LED. A valve connected to compressed air at 20 psi (138 kPa) was repeatedly opened and closed to
get the two robots to inch toward each other.
Fabrication and design of wearable system
A textile-­based capacitive strain sensor, as developed in our previous
work (65), was embedded into the elbow sleeve using the sleeve’s fabric as a dielectric layer. The two leads from the sensor were soldered
to a rigid capacitive sensor processing board (MPR121, Adafruit).
From this board, 5-­V, GND, and I2C lines were connected to thestretchable Arduino. Another LED breakout board was fabricated forthis demonstration. The serial communication lines from the Pro
Mini were connected to the FTDI programming board, which wasconnected through USB to a computer.
Laying the sleeve flat on a table, the Arduino was placed directly
over the top of the sensor and pressed into place. The LED breakout
board was placed next to it so that the GND and digital pins aligned
and the substrate overlapped by 1 mm. The header pin holes for thethree digital pins, LEDs, and GND were exposed on both the Arduino and the LED board, connected with more OGaIn, and thenencapsulated with rubber cement.
Statistical analysis
In each experiment, we have noted the number of times an experiment was independently performed (N). Where N > 2, shaded regions or error bars indicate one SD. For fit lines, R2 values are reported.
Units are listed for all measurements.

Supplementary Materials
The PDF file includes:
Methods
Figs. S1 to S13
Table S1
References (66, 67)
Other Supplementary Material for this manuscript includes the following:
Movies S1 to S7

REFERENCES AND NOTES
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April 2021; https://blog.arduino.cc/2021/04/13/the-­arduino-­forum-­is-­now-­completely-­renovated-­and-­its-­so-­nice/.
2.	Arduino, Uno R3; https://docs.arduino.cc/hardware/uno-­rev3/.
3. 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).
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exits, silicone tubes (5236 K203, McMaster-­Carr) were inserted withtweezers and secured with Sil-­Poxy.
To distribute the circuit design, the outline of the soft quadruped
robot designed above was imported into AutoDesk Eagle as a board
outline. The routing from the Arduino Pro Mini was then erased,
the components manually moved to the desired locations on theboard, and the autoroute feature in Eagle was used to create newroutes, including GND lines.
The DS10 quadruped circuit was fabricated using the same manufacturing procedure, but Slacker 1.5 was used as the substrate andencapsulant (fig. S12A). For both the Slacker and VHB tape circuits,
the I2C communication wires were added after the top was alreadyencapsulated to ensure that no traces were bridged during wire placement. To do this, tweezers pinched the encapsulant above the header
pin hole, and sewing scissors were used to snip a hole in the encapsulant. The wires were then attached the same way as described previously, and a dab of extra encapsulant was put over the wire lead.
The Slacker circuit was attached to the DS10 robot by coating athin layer of DS10 over the top of the robot and placing the circuiton top to cure (fig. S12B). The VHB tape circuit adhered loosely tothe robot, although the rubber cement did not adhere. At the tip ofeach leg, the circuit was mechanically bonded to the robot using
DS10 (fig. S12, C and D).
The quadruped setup (movies S3 and S4) was as follows: The soft
Arduino was connected to the laptop for the power supply and to
the I2C breakout board. The breakout board was connected to thepressure regulators. Compressed air was fed into the pressure regulators, the outputs of which went to each leg and the body. The
Arduino had a programmed gait that it ran by controlling the pressure regulators, using the I2C protocol.

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Acknowledgments: We thank L. Sanchez-­Botero for providing material for preliminary
experiments and engaging in discussions. Funding: This material is based on work supportedby the National Science Foundation under grant no. IIS-­1954591. S.J.W. was supported by aNASA NSTGRO Fellowship (80NSSC22K1188). D.S.S. was supported by a NASA SpaceTechnology Research Fellowship (80NSSC17K0164). A.A. was supported by an NSF Graduate
Research Fellowship (DGE-­2139841). Author contributions: R.K.-­B. conceived the project.
S.J.W. designed and executed all experiments and led the writing of the paper. D.S.S.
developed the initial manufacturing procedure. D.S.S. and R.K.-­B. contributed to the design ofthe experiments and data interpretation. M.L. contributed to fabricating and executing thequadruped and VoxelBot demonstrations. A.A. fabricated the sensor and helped execute thewearable demonstration. All authors contributed to the preparation of the manuscript.
Competing interests: S.J.W., D.S.S., and R.K.-­B. are listed as inventors on US continuation-­in-­part application no. 18/148,500, which claims priority to US Patent application no. 17/357,060,
on which D.S.S. and R.K.-­B. are also inventors. All other authors declare that they have nocompeting interests. Data and materials availability: All data needed to evaluate theconclusions in this paper are present in the paper or the Supplementary Materials. The dataand code for this study have been deposited in the Dryad database (https://doi.org/10.5061/
dryad.80gb5mkxf ), and additional resources, including design files, laser cutting files, a bill ofmaterials, and step-­by-­step instructions for creating your own stretchable Arduino, are on
GitHub at https://github.com/swoodman11/SoftArduino.
Submitted 21 December 2023
Accepted 12 August 2024
Published 11 September 2024
10.1126/scirobotics.adn6844

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