SCIENCE ROBOTICS | FOCUS
MATERIALS ROBOTICSWill robots be bodies with brains or brains with bodies?
Yiğit Mengüç,1*†‡ Nikolaus Correll,2*† Rebecca Kramer,3*† Jamie Paik4*†

Are robots simply machines thatbining distinct materials. There ex­run bits of code, or are they software
ist new fundamental scientific and“bots” interacting with the world
engineering questions related tothrough a physical instrument? The
how to fabricate, model, and designmaterial robotics community un­
the sensing, processing, and actua­
ravels the basic assumptions behindtion materials in a robotic system
this question by taking a third path:(4). Solving these challenges has theone that imbues intelligence into thepotential to accelerate the distribu­
very matter of a robot and removes
tion of robots into our daily lives
the dichotomy of brain versus body.
by making them more autonomous,
Examples of such material intelli­physically robust, easier to design,
gence abound in nature. Textured
and faster to manufacture (5).
camouflage skin follows the example
set by the cuttlefish’s ability to blend
GRAND CHALLENGES
into its environment (1). Spines andMaterial robotics research repre­sents
structured surfaces inspired by rem­the vertical integration of simple ca­ora suckers lead to strong underwa­
pabilities at the molecular or micro­
ter attachment (2). Hearts and colons
scale enabled by materials science
are autonomous systems that canthat turn into pragmatic robotic ap­
provide complex functionality likeplications at the human scale—a pro­pumping liquids or material support
cess that we loosely ascribe to five
without external control (3). Such
distinct activities: (i) materials syn­complexity motivates our researchthesis, (ii) mechanical design, (iii)and begs the question: Should it besys­tem integration, (iv) sensing andmaterials scientists or roboticists that
control, and (v) manufacturing.
“build” such systems? The answer
Examples of materials synthesis
is both.
include efforts to create novel mate­Because robots are placed in therial capabilities ranging from phasereal world, they must reliably androbustly measure, interpret, and re­ Fig. 1. Material-enabled robotics. A future robot’s body may combine soft change actuators and shape memory
to biocompatible conductors and bio­spond to variable environments and actuators and stiff structure, with distributed computation throughout.
degradable elastomers. These rep­
physical requirements. Material ro­
resent efforts to directly introduce
botics represents an acknowledg­
ment that materials can absorb some of the computational requirements from the cen­tral functional components at the material level andare closest in spirit and scope to traditional ma­
challenges of acting and reacting to an un­ processing system.
certain world. The spectrum of possible ap­
Two distinct approaches remain in creating terials science research.
Mechanical design uses the passive and non­proaches spans from soft grippers with zero composite materials that match the complex­
knowledge and zero feedback all the way to ity of functional biological tissue: new materials linear behavior of soft matter to enable capabil­humanoids with full knowledge and full feed­ synthesis and system-level integration of ma­ ities, such as snake-like undulatory locomotion,back (Fig. 1). Embedding distributed sensors terial components. We acknowledge the im­ gripping fingers that can twist, and jellyfish-­and actuators directly into the material of the mense advancements of materials science, but inspired swimming [see contents of the Ma­
robot’s body engages computational capabil­ the challenges in system integration are not terial Robotics workshop (6)]. The control ofities and offloads the rigid information and merely a technical matter of physically com­ these systems can often be markedly simpli­
fied by smart mechanical design, a concept1Collaborative Robotics and Intelligent Systems (CoRIS) Institute, Oregon State University, Corvallis, OR 97339,
also known as “morphological computation.”
23USA. Department of Computer Science, University of Colorado, Boulder, CO 80309, USA. Department of MeTrading off mechanical design with computa­
chanical Engineering, Yale University, New Haven, CT 06520, USA. 4Reconfigurable Robotics Laboratory, École
Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland.
tion, an idea just emerging in materials science,*These authors contributed equally to this work.
is deeply rooted in robotics, where mechanism†Corresponding author. Email: yigit.menguc@oregonstate.edu (Y.M.); nikolaus.correll@colorado.edu (N.C.);
design strongly affects the complexity of therebecca.kramer@yale.edu (R.K.); jamie.paik@epfl.ch (J.P.)
necessary control strategy.
‡Present address: Oculus Research, Redmond, 98052 WA, USA.
Mengüç et al., Sci. Robot. 2, eaar4527 (2017)29 November 2017

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CREDIT: ELLA MARU STUDIO

Biology motivates how complex functionality results from systems of simple materials.

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The Authors, somerights reserved;
exclusive licensee
American Associationfor the Advancementof Science. No claim
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Mengüç et al., Sci. Robot. 2, eaar4527 (2017)

ing and casting are accessible but require a great
deal of skill to create a reliably functional soft
robot. Nonlinear material properties such as
hyperelasticity and viscoelasticity make small
manufacturing defects, such as an inconsis­
tent wall thickness in an elastic membrane,
extremely sensitive to operating conditions.
New techniques in rapid manufacturing draw
heavily from materials sciences to facilitate
scientific replicability in robotics. Thus, ef­
forts in three-dimensional printing are great
examples of such a collaboration where un­derstanding materials and controls is equallyimportant and can directly facilitate further
acceleration of material robotics research (10).
THE PATH FORWARD

Material robotics as a field has proliferated inpart because of the ease of access to the meth­ods and materials. As a young field being built
on the novelty of repurposing technologies,
the low barrier to entry has enabled materials
scientists and roboticists alike to establish acommon foundation. However, we have now
established only proofs of concept. The pathforward is transitioning these concepts to appli­
cation context, which will require tight integra­
tion of sensing, actuation, and computational
functions into materials that embody learningand control. Materials scientists are developing
new bulk materials with inherent multifunc­
tionality sufficient for robotic applications. Ro­
boticists are developing new material systems
with tightly integrated components. The con­vergence of these approaches will ultimately
yield the next generation of material-enabledrobots. We see the burgeoning community as a29 November 2017

natural partnership that will lead to robots
with brains in their bodies—the foundation ofinexpensive and ubiquitous robots that will
step into the real world.
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10.1126/scirobotics.aar4527
Citation: Y. Mengüç, N. Correll, R. Kramer, J. Paik, Will robots
be bodies with brains or brains with bodies?. Sci. Robot. 2,eaar4527 (2017).

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System integration resembles traditional
robotics effort but with notable emphasis on
incorporating heterogeneous materials andfunctionalities (7). Prototypical examples ofsystem-level efforts include integrating sen­sors, computation, energy storage, and wire­
less communication into substrates such as
rubber to enable smart tires and soft grippers
capable of identifying the traction character­istics of different surfaces and grasps, respec­tively. Integration of actuation and sensing andcontrol into elastic polymers and fabrics resultsin active “skins” that produce locomotion andmanipulation behaviors based on the shape of
the passive structure that is enveloped (8).
Sensing and control represent the processesof controlling new materials’ actions. Estab­lished techniques of modeling material prop­
erties are limited when applied to time- anduse-variant materials. We therefore require
new materials with tightly integrated sensing
and actuation, as well as new approaches lever­aging machine learning, to achieve feedback
and model-predictive closed-loop control (9).
The results of these efforts will lead to con­trollers capable of exploiting material non­linearity in locomotion of and manipulation
by soft-bodied robots.
Manufacturing represents the largest plu­
rality of current research, and considering its
prevalence to some degree in nearly everyre­search effort, we consider it a foundational
topic in the community. For example, system
integration as a topic is strongly coupled to
new techniques in manufacturing: Embedding
integrated circuit electronics into soft materials
addresses manufacturing challenges and neces­sary mechanical gradations of stiffness. Mold­

Will robots be bodies with brains or brains with bodies?
Yigit Mengüç, Nikolaus Correll, Rebecca Kramer and Jamie Paik

Sci. Robotics 2, eaar4527.
DOI: 10.1126/scirobotics.aar4527

http://robotics.sciencemag.org/content/2/12/eaar4527

REFERENCES

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