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Multifunctional Materials
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Roadmap on soft robotics: multifunctionality, adaptability
and growth without borders
Barbara Mazzolai1,∗, Alessio Mondini1, Emanuela Del Dottore1, Laura Margheri1, Federico Carpi2,Koichi Suzumori3, Matteo Cianchetti4,5, Thomas Speck6, Stoyan K Smoukov7, Ingo Burgert8,9,Tobias Keplinger8,9, Gilberto De Freitas Siqueira9, Felix Vanneste10, Olivier Goury10,
Christian Duriez10, Thrishantha Nanayakkara11, Bram Vanderborght12, Joost Brancart12,
Seppe Terryn12, Steven I Rich13, Ruiyuan Liu14, Kenjiro Fukuda13,14, Takao Someya13,14,15,
Marcello Calisti16,17, Cecilia Laschi18, Wenguang Sun19, Gang Wang19, Li Wen19,Robert Baines20, Sree Kalyan Patiballa21, Rebecca Kramer-Bottiglio20, Daniela Rus21,Peer Fischer22,23, Friedrich C Simmel24 and Andreas Lendlein25,26
1Bioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Italy
Department of Industrial Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy
3
Department of Mechanical Engineering, Tokyo Institute of Technology, Ookayama, Meguro, Tokyo 152-8550, Japan
4
The BioRobotics Institute, Scuola Superiore Sant’Anna, 56025 Pisa, Italy
5
Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, 56025 Pisa, Italy
6
Plant Biomechanics Group & Botanic Garden, and Cluster of Excellence livMatS @ FIT, University of Freiburg, Germany
7
Active and Intelligent Materials Laboratory, Queen Mary University of London, London E1 4NS, United Kingdom
8
Wood Materials Science, Institute for Building Materials, ETH Zurich, 8093 Zurich, Switzerland
9
Cellulose and Wood Materials Laboratory, Empa, Swiss Federal Laboratories for Materials Science and Technology, 8600 Dübendorf,
Switzerland
10
University of Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France
11
Dyson School of Design Engineering, Imperial College London, United Kingdom
12
Vrije Universiteit Brussel and imec, Brussels, Belgium
13
Thin-Film Device Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
14
Center for Emergent Matter Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
15
Electrical and Electronic Engineering and Information Systems, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656,
Japan
16
The BioRobotics Institute, Scuola Superiore Sant’Anna, Italy
17
Lincoln Institute for Agri-food Technology, University of Lincoln, Lincoln, United Kingdom
18
Department of Mechanical Engineering, National University of Singapore, Singapore
19
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, People’s Republic of China
20
Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut 06511, United States ofAmerica21
CSAIL, MIT Schwarzman College of Computing, United States of America
22
Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart, Germany
23
Institute of Physical Chemistry, University of Stuttgart, Pfaffenwaldring 55, Stuttgart 70569, Germany
24
Physics Department E14, Technical University Munich, 85748 Garching, Germany
25
Institute of Active Polymers, Helmholtz-Zentrum Hereon, Teltow, Germany
26
Institute of Chemistry, University of Potsdam, Potsdam, Germany∗
Author to whom any correspondence should be addressed.
2E-mail: barbara.mazzolai@iit.it
Keywords: robotics, soft robotics, robot, actuation, sensor, roadmap, self healing

Abstract
Soft robotics aims at creating systems with improved performance of movement and adaptability
in unknown, challenging, environments and with higher level of safety during interactions withhumans. This Roadmap on Soft Robotics covers selected aspects for the design of soft robots
significantly linked to the area of multifunctional materials, as these are considered a fundamental
component in the design of soft robots for an improvement of their peculiar abilities, such asmorphing, adaptivity and growth. The roadmap includes different approaches for components andsystems design, bioinspired materials, methodologies for building soft robots, strategies for the
implementation and control of their functionalities and behavior, and examples of soft-bodied© 2022 The Author(s). Published by IOP Publishing Ltd

Multifunct. Mater. 5 (2022) 032001

B Mazzolai et alsystems showing abilities across different environments. For each covered topic, the author(s)describe the current status and research directions, current and future challenges, and perspective
advances in science and technology to meet the challenges.

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1. Soft robotics: new generation of adaptable, self-morphing, growing robots
2. Electro-responsive elastomeric actuators
3. Soft hydraulic muscle
4. Variable stiffness technologies for soft robotics
5. Materials systems for soft robotics and architecture inspired by plants
6. Sustainably grown: the underdog robots of the future
7. Wood and cellulose composites for material optimisation
8. Shape-memory polymers and actuators for soft robotics
9. Modeling soft robots
10. Realtime mechanical impedance control in soft robots for information gain and efficient control
11. Self healing soft robots
12. Power sources for soft robots
13. Plantoids and self-growing soft robots
14. Underwater soft robots
15. Multifunctionality, adaptability and growth without borders
16. Amphibious robots with morphing limbs
17. Future undersea observatories with soft robotic instruments
18. Nanoscale soft robots
References

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Introduction
1. Soft robotics: new generation of adaptable, self-morphing, growing robots
Barbara Mazzolai, Alessio Mondini, Emanuela Del Dottore and Laura Margheri
Bioinspired Soft Robotics Laboratory, Istituto Italiano di Tecnologia, Italy
Overview
Soft robotics aims at creating systems with high level of adaptability for operations in unknown andchallenging environments and where a safer human-robot interaction is needed.
With the increasing vision of using robots beyond the structured industrial context, the spectrum of
applications of soft machines is becoming remarkably broad. From natural environment exploration tohuman-made infrastructure inspection, from medicine to space, soft robots are of major interest because of
their peculiar abilities of morphing, perception-based behavior, highly dexterous manipulation and versatilegripping, adaptive locomotion, anchoring, adhesion, and growing.
Much of the research in soft robotics is linked to biomimetics, thus living organisms are often considered
as a model, because they are masters to put in place simplifying principles that make their sensory-motor
behavior efficient and highly flexible to respond to dynamic changes. The secret of natural systems lies in thesmart characteristics of how their body is designed and in how their intelligence is embodied and distributed
in it, allowing them to effectively adapt, grow and survive. And here lays the link with soft robotics: similarly,
soft robots benefit of the use of smart and multi-functional materials (gels, elastomers, biological materials,etc) and of a body compliant with the external environment. Intelligence is also integrated in the body(‘embodied’) and co-develops with it, emerging from the interaction of the body itself with the world. Thisway, soft robots’ sensory-motor behavior becomes more efficient in responding to dynamic changes, as forliving organisms.
Started in the years 2006–2008 as a niche of robotics, soft robotics is now a well-known sector, with aproactive and well-connected community of researchers world-wide [1]. Not only robotics engineers, butalso biologists, computer scientists, mathematicians—just to mention a few—are part of the community ofsoft robotics.
Particularly relevant, is the link between soft robotics and material science and the mutual benefits thatthe corresponding communities are reaching. Using soft, multi-functional, material structures for the designof new forms of actuation and sensing, together with new modeling and control architectures, soft robots
have been allowed to achieve different abilities such as jumping [1, 2], peristaltic locomotion [3], elongationand shortening [1], climbing [4], stretchability [5], adaptable grasping [6, 7], combined bending andstiffening [8], flying [9, 10], self-healing (SH) [11], self-morphing and growing [12].
For consolidating and pushing forward the abilities of soft robotic components and systems, a deep effort
is necessary towards an advancement of materials chemistry, mechanics, as well as novel fabrication
techniques for systems development and robust materials interfacing. A cross-fertilization of disciplines thatis beyond the currently widely claimed multidisciplinary approaches, guiding a design that merges together
aspects of the natural and the digital environment.
Roadmap organization and aim
With a highly multi-disciplinary background of scientific and technological sciences, this Roadmap on Soft
Robotics aims at covering some of the major aspects of components for the design of soft robots andespecially of the role of multi-functional materials in improving soft robots’ behaviors and peculiar abilities.
The roadmap includes different sections with a description of current status, current and futurechallenges, and a perspective of needed advances in science and technology to meet the challenges fordifferent components and systems.
Experts in technologies for soft actuators design and development, bioinspired materials, control of soft
robots’ functionalities and behavior, and design of soft-bodied systems at macro and nanoscale, havecontributed to this work.
The main objective of this document is to give an overview of the current state of the art of the field andto draw the attention on the main challenges that researchers could tackle to advance the area with bothscientific and technological impacts.
The intended audience includes both young researchers and students that are approaching the topic, andexperienced researchers that are interested in having a reference and reading about possible open questions
and perspectives.
Thanks to the multi-disciplinary characteristics of the field of soft robotics, all the sections could be
relevant for many areas of engineering, as well as for material science, biology, or computer science.
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Open challenges and perspective
Soft robotics is still in its first ramp-up phase of research in terms of technological maturity and systems
applicability. Since the first years, the field has been characterized by a multi-facet scenario, investigating
unconventional materials, studying the relations between morphologies and functionalities, challenging
problems of self-organizations, self-stability and self-assembly [13].
This multi-disciplinary mark is still maintained, as demonstrated along this Roadmap, encompassing
new technological solutions and challenges for multi-functional bioinspired materials, different types of softand variable stiffness actuators, new models of control architecture, and presenting integrated systems frommacro to micro scales. This is a core feature for the field, and a fascinating characteristics for all the
researchers who come from different sectors and can meet and share different know-how.
In soft robotics, the link across the research for innovative technologies and the pursue of scientificdiscoveries with biological investigations on natural models is strong and bidirectional.
Looking at the living world and taking inspiration from natural behaviors, adaptive morphologies,
energy-consumption strategies—which are all at the core of the soft robotics research—represent thefundamental steps towards the design of a new wave of robotic solutions that are not only more relevant inreal-world scenarios, but also more sustainable.
As soft robots are on the rise with a lot of promising applications, we need not only to pose and respondto new ethical and legal questions, but also deal with ecological and global health issues. The community ofrobotics is in fact starting to discuss more deeply how to design the new generations of technologies in order
to be better integrated in our world without affecting it, energetically or with new tons of e-waste [14–16].
Soft robotics can be a game changer to effectively design artificial systems with a null impact in the
biological world. Soft bioinspired robots of the future will be able to adapt and evolve, will be made ofrecyclable or biodegradable or biohybrid materials, and will use renewable forms of energy without weighingon the natural ecosystems energy balance.
Similarly to natural systems, these green soft robots will be developed to follow a life-like circle and tobetter integrate into the natural ecosystem, creating a new wave of environmentally-responsible machines
[15].

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2. Electro-responsive elastomeric actuators
Federico Carpi
Department of Industrial Engineering, University of Florence, Via di S. Marta, 3, 50139 Florence, Italy
StatusAmong Electromechanically Active Polymers, which are ‘smart materials’ that deform in response toelectrical stimuli, dielectric elastomer (DE) actuators [17] show the greatest potential for soft mechatronics[18]. They are capable of large electrically-induced strains and stresses, in some cases exceeding those of
mammalian muscles [19]. As compared to electromagnetic motors, DE actuators (DEAs) have low specificweight, high energy density, fast response, self-sensing ability, scalable performance, low power consumption
and silent operation, as well as an intrinsic mechanical compliance, which can also be electrically controlled[18].
An elementary DEA consists of a soft insulating membrane (made of silicone, acrylic or otherelastomers), coated on either side with a compliant electrode material (e.g. carbon-loaded silicone), so as toobtain a deformable capacitor. When a voltage is applied between the electrodes, electrostatic forces squeeze
the membrane, causing a reduction of its thickness and an increase of its surface (figure 1).
The effective compressive stress p can be quantified as [17]:( )2Vp = ϵr ϵ0 E = ϵr ϵ0
d
2

(1)

where ϵ0 is the dielectric permittivity of vacuum, ϵr is the elastomer’s relative dielectric constant, E is theelectric field, V is the voltage and d is the membrane’s thickness.
Due to their large electrical deformability, DEAs are studied as ‘artificial muscles’, especially forbioinspired machines. Examples include robotic fingers, grippers and arms, tuneable lenses for robotic
vision, as well as terrestrial (legged, crawling and hopping), aerial and underwater robots [20]. As an
example, figure 2 shows a hexapod robot [21], having soft legs made of the artificial muscle itself, such thatstructure and actuation were fused together. Each leg was a spring roll DEA, with multiple electrodes, which
could be individually driven, so as to create bending motions according to multiple degrees of freedom. Thissolution, which is not possible with conventional motors, demonstrates how soft machines can simplify
robotic design, avoiding complex mechanisms and reducing weight.
Current and future challenges
Due to non-linearities deriving from their hyper-visco-elastic properties, DEAs require special control
strategies. These are still largely unexplored and, in the opinion of the author, their challenges are analogous
to those for accurate control of the most used Soft Robotics technology, i.e. soft pneumatic actuators. Indeed,
they are both based on hyper-visco-elastic bodies.
However, DEAs also raise distinctive challenges. One of them deals with attempts to harness
electromechanical instabilities (especially snap-through instability), in order to obtain giant actuation
strains; whilst feasibility has been proven [23], applicability to the majority of DEA-based devices andapplications is not straightforward, requiring further developments. Differently, recent progress inaddressing the following two additional challenges is showing interesting outcomes, with wide applicability.
High voltages
As a main limitation, DEAs need high driving voltages (typical order of 1 kV), which have the following
implications.
In terms of electrical safety, the drawback is mitigated by the electrostatic principle of operation, which
requires low currents. This allows for using electrically safe low-power sources [18].
In terms of size of the electronics, the low power requirement enables the use of compact, portable,
battery-operated units [18]. However, any electronics in the kV range will always be bulkier (due to need forinsulations) and more expensive (especially due to a lower market share) than any electronics working at
one-order-of-magnitude lower voltages.
These limitations scale up as the number of degrees of freedom (i.e. independent DEAS) to be controlled
increases, as they need either independent channels or ad-hoc strategies, such as multiplexing from a single
high voltage source via high voltage transistors.
Overcoming such issues requires a reduction of the voltages in the range below 500 V, where highly
compact electronics suitable for DEAs has been demonstrated [24]. Moreover, a few hundred Volts are
typical for the low-size and low-cost electronics of common products like piezoelectric actuators.
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Figure 1. Working principle of an elementary DEA.

Figure 2. Example of a bioinspired robot using dielectric elastomers both as structural components (legs) and actuators(muscles). Reproduced from [22]. © IOP Publishing Ltd. All rights reserved.

Low forces
In order to actuate systems that have a size in the millimetres-centimetres range and have to be compact,
lightweight and energy efficient, DEAs have significant advantages over conventional actuators. However,when it comes to large-scale and large-force systems, DEAs cannot compete with traditional electromagnetic,
pneumatic or hydraulic drives. As the actuation performance is a direct consequence of the constitutive
matter and physical principle of operation, clearly any technology always has an ideal range of optimal use.
Nevertheless, attempts can be made to try to somewhat extend that range. For DEAs, increasing the
maximum force output is a challenge addressed with various strategies, as discussed below.
Advances in science and technology to meet challenges
Reduction of the driving voltages
In order to reduce the voltages, according to equation (1) there are two approaches: (a) a long-term strategy
is at the level of material synthesis and targets new elastomers with a higher dielectric constant [25]; (b) ashort-term strategy is at the level of material processing and aims to manufacture thinner membranes.
In order to implement these strategies, the best materials of choice (in terms of environmental stability,
reliability, versatility and low cost) currently are silicones. Even with off-the-shelf compositions, thepossibility to reduce the thickness down to a few microns, while keeping adequate actuation capability, hasbeen demonstrated [26]. This shows that DEA operation at a few hundred Volts might soon become
standard practice, enabling more compact and cost-effective electronics.
As a downside, however, thinner membranes will require stacking of multiple layers, so as to preserve adesirable elastic force of the actuator. Therefore, multi-layer manufacturing is expected to play a key role in
the future.
Increase of the output force
In order to increase the forces, two approaches have been described. The first one consists in combining a
DEA membrane with springs acting as biasing elements able to amplify displacements and forces. A key
breakthrough has recently been achieved with cone-shaped DEAs made of stacked membranes combinedwith a bi-stable mechanism, consisting of linear bias springs and negative-rate bias springs: an
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86 × 86 × 25 mm3 actuator was able to produce a displacement of ∼3 mm and a force of ∼100 N, which was∼200 times greater than the force achievable from conventional membrane DEAs [27].
A second strategy to increase the forces consists in combining DE actuation with electro-adhesion. A
remarkable improvement has been achieved for bending-type DEAs wrapping around an object (e.g. forgrasping), using a modified design of the electrodes, which enhanced the fringe electric fields at their edges:
the fringe fields were able to significantly polarize the object’s surface, so as to generate attractive(electro-adhesive) forces, exchanged with the electrodes’ charges; with this approach, a low DEA force(1 mN) was complemented with a high electro-adhesive holding force (3.5 N shear force for 1 cm2 ), greatly
improving the grasping performance [28].
Concluding remarks
DEAs offer significant opportunities to develop electrically controlled bioinspired robotic machines. Theyadvantageously enable effective mimicry of biological ‘behaviors’ (e.g. types of motions) and properties (e.g.
in terms of combination of structure and function), to an extent and with a level of integration that are notpossible with any conventional actuation system. Indeed, even in comparison with soft pneumatic actuators(as the most used technology in Soft Robotics), DEAs offer a unique combination of a soft body with directelectrical driving, overcoming the typical limitations of bulky driving units.
However, as compared to pneumatic actuators and other motors, DEAs require higher voltages andgenerate lower forces. Although successful strategies to circumvent these limitations have been
demonstrated, DEAs appear today more suited as a complementary, rather than alternative, technology tothem. Indeed, its advantages become progressively more evident as the size of the systems reduces, whilst
conventional technologies increasingly show their limitations towards miniaturization.

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3. Soft hydraulic muscle
Koichi Suzumori
Department of Mechanical Engineering, Tokyo Institute of Technology, Ookayama, Meguro, Tokyo
152-8550, Japan
StatusSuzumori proposed a new field in soft robotics, Power Soft Robotics [29]. One might think that soft robots
generally have poor at power and force capacity, which results in safety and shape-adaptability, although thisis not correct because power and softness are independent ideas and it is possible to realize robots that haveboth softness and power. Many examples that show both power and flexibility can be found in nature. The
elephant trunk deforms very flexibly while it works very powerfully, giraffes fight by attacking each other’s
necks while the necks work flexibly at the same time to absorb the dynamic energy to protect themselves, andsnakes kill animals that are bigger than their body by strangling them. Suzumori believes that power soft
robotics is one of the most promising new fields in soft robotics, by which powerful and gentle rescue robots
can be realized.
A key component in realizing Power Soft Robotics is a powerful and soft actuator. In particular, thehydraulic McKibben muscle is one of the most promising actuators currently in use. The McKibben muscle isone of the oldest artificial muscles [30] and is well-known and widely used today. It consists of a rubber tube
and braided cords around the tube. Applying fluid pressure to the rubber tube results in expansion of therubber tube in the radial direction, changing the blading angle of the bladed cords and causing the muscle tocontract in the axial direction. Most specimens are driven pneumatically with air pressures lower than
0.7 MPa. Pneumatics higher than 0.7 MPa is not generally used [31] because highly compressed air easily
stores big energy in it, which would have potential danger such as explosion and instantaneous unstablemotion of actuator [32], while hydraulics can generally use a much higher working pressure, i.e. 7–35 MPa
because of high incompressibility of water/oil. Applying high-pressure hydraulics to the McKibben muscles
has great potential for pioneering Power Soft Robotics.
Several Mckibben muscles driven by a hydraulic pressure of approximately 5–7 MPa have been developed[33, 34]. Figure 3 shows an example of these, which can generate a maximum contracting force of 11.5 kN
and a maximum contracting ratio of 30% by applying hydraulic pressure of 7 MPa.
Current and future challenges
There have been several other studies on hydraulic McKibben muscles, but most of them are driven withpressures lower than 1 MPa [35]. As the contracting force is proportional to the applied fluid pressure, higher
pressure is essential to demonstrate the hydraulic muscle’s advantage. In our research team, we are working
for hydraulic McKibben muscles driven by 10 MPa hydraulics using a new rubber material.
There are still several major issues and challenges. One issue is the material of the rubber tube, which
requires physical strength and good elasticity: resistance to high pressure and large deformation ability,
durability with respect to repeated deformations, small non-linearity, small hysteresis, and small creep
behavior [36]. In the case of oil hydraulics, oil resistance is also essential. In addition, chemical resistance toweatherability is also very important. For example, resistance to ultraviolet light or low/high temperature isrequired in some environments where power soft robots will work. Because soft materials used in soft robots
show generally poorer performance with respect to physical/chemical durability in comparison with stiff
materials used in conventional robotics, material science should play a large role in soft robotics.
Hydraulics include oil hydraulics and water hydraulics. Generally, oil hydraulics are currently more
popular for hydraulic actuators because there are various commercial components for oil hydraulics, and it ismuch easier to design oil hydraulic control systems than water control systems. However, most polymer
materials have poor oil resistance, and the development of good rubber materials for McKibben muscles is an
important issue.
The development of a compact hydraulic control system is another technical challenge. For example,
small, cheap, energy-efficient pumps and servo valves are necessary. In the case of water hydraulics, rustproof
control devices working under low lubrication conditions are necessary [37]. Flexible and thin hoses andsmall couplers, especially multi-channel swivel joints or slip rotating joints, are also challenging issues. In
addition, all these devices are expected to be soft.
A power soft robot design method that fully takes advantage of hydraulic soft muscle properties isanother challenge because it requires unique ideas that differ from conventional robot designs.
Advances in science and technology to meet challenges
Several studies of rubber materials with good strength and good elasticity, which include resistance to highpressure, large breaking elongation, high durability, small non-linearity, small hysteresis, and small creep
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Figure 3. An example of hydraulic McKibben muscles [34]. Normal status with no hydraulic pressure applied (upper figure),
where the outer diameter of the muscle is 13 mm. Contracting status (lower figure), where a hydraulic pressure of 7 MPa isapplied; the muscle contracts to 30% of the original length.

Figure 4. Examples of power soft robot applications of soft hydraulic muscles. Knee support device based on four-bar linkage andhydraulic artificial muscle [4] (left), rotational-compliant joint with hydraulic McKibben artificial muscles [42] (middle), andlong bending rubber arm combining contracting and extending muscles [40] (right). Reproduced from [41]. CC BY 4.0.

behavior, have been conducted for use as a muscle tube [33, 34], resulting in several hydraulic McKibben
muscles as shown in figure 3. Research is still ongoing to improve the rubber properties.
To maintain muscle softness under higher applied pressure, bundling thin muscles instead of using one
thick muscle is a good approach. As the contraction force depends on the cross-section of the muscles or the
total cross-sectional area of each bundled muscle, bundled muscles generate a force of approximately 80% of
one muscle that has the same diameter because some dead areas exist between the thin muscles that do notcontribute to the contraction force. While the force decreases by 20% with bundling, bundling realizes acontracting ratio larger than that of the original muscle. These interesting phenomena have been reported inpneumatic McKibben muscles [38, 39] and can be applied to hydraulic muscles. In this sense, extrusion
molding processes of thin rubber tubes and the bundling process are now ongoing.
Many hydraulic devices for hydraulic control, such as pumps, valves, hoses, and couplings, have also beendeveloped [34]. However, most of them were developed for larger and higher-pressure hydraulics. Miniaturedevices for lower-pressure systems than conventional hydraulics are required. In addition, new devices with
soft bodies would greatly contribute to totally soft hydraulic muscles.
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Figure 4 shows examples of soft power robots consisting of soft McKibben hydraulic muscles. To design apowerful long arm, shown in the right picture in figure 4, for example, combining contracting and extending
muscles is essential. In general, a cantilever requires two portions on its cross-section to resist the bending
moment: a portion supporting compressive stress, and a portion supporting tensile stress. The existence ofboth realizes bending stiffness and a bending moment [40]. In the elephant trunk, the same mechanism isinvolved. This type of unique design method to take advantage of hydraulic soft muscle properties isimportant for realizing power soft robots.
Concluding remarks
I believe that power soft robotics is a new, promising research field is, in which new soft robots with powerand softness can be realized. For this purpose, soft hydraulic muscle is a key device. I believe that rubbermaterials, soft and miniature fluid control devices, and system integration methods are key technologies torealize power soft robots.

Acknowledgments
The work shown in this section was partially supported by JSPS KAKENHI Grant Numbers JP18H05465,
JP18H03760, 26249028, and the ImPACT Program of the Council for Science, Technology, and Innovation.

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4. Variable stiffness technologies for soft robotics
Matteo Cianchetti
The BioRobotics Institute, Scuola Superiore Sant’Anna, 56025 Pisa, Italy
Department of Excellence in Robotics & AI, Scuola Superiore Sant’Anna, 56025 Pisa, Italy
Status
The ability of varying the stiffness of a material or of a mechanism in a robot originates as a directconsequence of the use of soft and compliant materials in soft robotics. While on one side the use of soft
materials enables a series of unprecedented capabilities, in general it also limits the maximum force that the
robot can exchange with the environment. Excluding those cases where deformability, dexterity and intrinsic
safety are important and sufficient for the intended task (e.g. morphing, inspection), usually it is necessarythat the soft/compliant systems vary their stiffness. Tunable stiffness can be used to improve stability andforce application, but it can also enable selective reconfigurability and variable kinematics(blocking/releasing degrees of freedom).
A stiffness variation can be obtained in three ways:• Stiffening by deformation. An active soft actuator usually exploits its deformation to generate mechanicalwork and this deformation, in turn, causes a material stiffening;• Stiffening by antagonistic activation. Active actuation technologies combined in pairs so that their action
is equal and opposite to each other results in no deformation of the overall system, but with increase of
stiffness;• Stiffening (or softening) by variation of intrinsic properties. There exist some physical principles that canbe exploited to develop semi-active actuation technologies.
The third option is gaining increasing attention, because it potentially provides higher compactness and it isdecoupled from deformation. Moreover, these technologies can be also used as recoverable mechanical fuses
and for mechanical energy dissipation. This group includes: shape memory materials (SMMs), electro- ormagneto-rheological fluids (ERFs or MRFs), jamming transition (JT) and low melting-point materials(LMPMs). Note that, all these technologies increase the stiffness upon activation, except the last one, whichon contrary softens.
Current and future challenges
Soft robotics is still at its infancy in terms of technological maturity and variable stiffness technologies areeven younger. For this reason the current main challenges are related to the classic elements to be mastered inorder to exploit a physical principle behind an observed macroscopic behavior as a new actuation technology[43]: (a) model the phenomenon; (b) explore material aspects; (c) develop a complete concept, including any
structural involvement.
Optimal results on the material aspects have been already achieved in the study of SMM, but the researchis still very much on the definition of usable and reliable models to describe the phase transformation
phenomenon, which is very complex for the number of parameters involved in the process [44], although
their use as variable stiffness systems (i.e. without involving deformation) slightly simplifies the approach.
Modeling is also the major limit of technologies based on JT [45]. The phenomenon is easy to observe,
but more complex to be used properly. Modeling involves the description of interaction among several
parameters of both the filler and the containing membrane, but the most limiting factor is represented by thedifficulty in predicting the packing of the filler inside the membrane. This is easier for fiber and layer
jamming provided that regular shapes and a limited amount of elements are used [46, 47], but it is very
complex for granular jamming. Distinct Element Modeling (sometimes combined with Finite Element
Modeling) and probabilistic approaches remain the only possibilities.
LMPM are based on simple phase transformation phenomena, thus the current challenges are mainly
related to material science research aiming at achieving high stiffness variability with the lowest amount ofprovided heat. However, an adequate and complete structural concept is still under investigation,
considering that the principle is based on the material passing from solid to liquid (and vice versa), that thus
needs encapsulation too [48].
ERF and MRF suffer from the same encapsulation limitation, although the concept has been also
extended to elastomers and networks [49]. For this class, materials reached a good level of maturity, but
providing the triggering field still remains a bottleneck, since they require high electric voltages or the
integration of (usually bulky) electromagnets.
12

13

Low
melting-pointmaterials

Jammingtransition

RheologicalfluidsShapememorymaterials

Technology

Alloys
Wax
Polymers

Fiber
Layer

GranularMagneto-Electro-Polymers

AlloysPhasetransition

FrictionvariationPhasetransition
Glass
transition
Viscosity
variation

Physicalprinciple

Heat

Electric
field
Magnetic
field
Fluid

Heat

Trigger

5×
10–37×
40×

101 W
100 W
102 W

100 W

102 MPa

2–102 ×

101 W

101 MPa
101 MPa
102 kPa
101 kPa
10◦ MPa

5×
10×
25–104 ×
103 ×
86×

Seconds to minutes(seconds tominutes)

Structure (simple structures do not
fully exploit the technology potential)
Material (maximize phase transition
velocity without compromising
stiffness variation)

Model (complex interaction among
multiple parameters)

Seconds (fraction of
seconds)

10◦ MPa

Material (high electric field)

Model (complex interaction among
multiple parameters)

Major current challenge

Structure (inclusion of electromagnets)

Fraction of seconds(seconds)
Seconds to minutes(seconds)
Fraction of seconds(N/A)

Increase (decrease)
stiffness velocity

102 mPas

101 mPas

101 GPa

8–10×

102 W

Soft state orderof magnitude

Variation
range

Energyconsumption

Table 1. Summary of the characteristic performances of the main variable stiffness technologies (data adapted from [50–52]).

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Advances in science and technology to meet challenges
The main characteristics of the analyzed variable stiffness technologies are reported in table 1 along with thelimitations identified in the previous section and labeled under one of three aforementioned elements.
The limitations mentioned in modeling, often lead researchers to a trial-and-error approach, which canuse direct comparison of results to identify trends or general design rules. On the other side, this method not
only lacks of optimality, but reveals a further necessary advancement: the standardization of testing. Toooften results are very different or even contradictory due to different testing conditions and interpretation ofdata.
Limitations related to materials are usually the result of a necessary compromise between mechanical andelectrical (i.e. ERF) or thermal properties (i.e. LMPM), which can affect both the initial stiffness value andthe variation range.
Structural design limitations refer to the necessity of elaborating novel design solutions to enhance thebasic transduction principle and should aim at facilitating integration also at small scale. Fabrication is thus
another important factor that requires improvements, especially for those technologies that involve manualsteps or assemblies. However, the use of modern manufacturing techniques (such as additive
manufacturing), which are more and more pervasive and affordable, could provide precise and repeatableproduction processes.
Unmet challenges also lead to devices that are not efficient and present high power consumption.
However, while for ERF it is depending on material properties and structural design where there is room for
improvement, for SMM and LMPM, efficiency is intrinsically low due to the underlying thermal principle
exploited to obtain variable stiffness. Moreover, JT requires a different analysis and it is often subject of
debate, because its efficiency depends on whether the fluidic source is included in calculations. The necessityof a further external device remains also a limiting factor on the portability of JT-based systems. Somesolutions based on micro pumps have been proposed, but always negotiating with performances in terms of
response time and generated pressures. Anyhow, in principle, a major advantage of this kind of systems
remains related to the possibility to maintain stiffening without consuming energy (simply using normallyclosed valves).
Concluding remarks
The advancement rate related to variable stiffness technologies is nowadays very high, thanks to the growinginterest gained by soft robotics and related technologies. However, in general, their level of readiness is not
yet sufficient for being sustainable on large-scale applications.
To speed up the process, accuracy on terminology and standard procedures to interpret and report data
may be extremely useful. ‘Stiffness’ (or ‘rigidity’ if referred to an overall and omnidirectional increase ofresistance to mechanical deformation) is well-suited to define the behavior of the system in the elastic
regime, but it should be noted that all these technologies can easily exceed their yield stress (sliding in JT,
yielding in LMPM, flowing in ERF and MRF, stress induced phase transition in SMM). Although usually it is
not easy to identify the separation point between the two domains, it would be important to include thesedata in the evaluation of variable stiffness technologies. Moreover, this transition leads to apparent andrecoverable plasticity, which absorbs and dissipates energy. This further important functionality would
deserve more attention to be better exploited.

Acknowledgments
This work was partially supported by the European Union’s Horizon 2020 research and innovation
programme through the SoftGrip Project under Grant Agreement No. 101017054.

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5. Materials systems for soft robotics and architecture inspired by plants
Thomas Speck
Plant Biomechanics Group & Botanic Garden, and Cluster of Excellence livMatS @ FIT, University ofFreiburg
StatusPlants are not the first choice if one looks for inspiration in bioinspired materials systems to be applied insoft robotics or motile structures in general. However, plants offer a plethora of inspirations, which are often
overlooked as plant movements are typically too slow (e.g. growth processes) or too fast (e.g. motile traps incarnivorous plants) to be detected by the human eye [53]. Especially in the last two decades plant movements
and the underlying structures have attracted increasing interest for the development of bioinspired materials
systems [54, 55]. Detailed analyses of the form-structure-function relationships of plant tissues and organs,whose hierarchical structuring comprises up to ten orders of magnitude, and their scale overarchingmechanical properties [56] allow the transfer of previously little-used or even unknown properties into novel
bioinspired materials systems [54]. These developments include plant-inspired materials systems with highload-bearing and pronounced energy dissipation capacity at little mass [57], with various self-x-properties,
as e.g. self-repair [58] or self-cleaning [59], but also motile systems for various fields of application in
soft-robotics [60] and green architecture [54]. Of special importance for bioinspired compliant and motile
materials systems as used in soft robotics and façade-skins is the finding that plants typically performmovements without localized hinges but by elastic deformation of larger regions of their tissues or organs(Figure 5 and 6) [53–55]. By this, stress concentrations, which are typical for pivot points in animal andconventional technical joints, are avoided and these plant structures are less prone to failure caused byoverload and/or pronounced wear. For future technical applications, more studies on and an increasing
development of plant-inspired material systems in general and mobile systems in particular will lead not only
to more durable (e.g. less wear and tear and self-repair) but also to ‘greener’ (e.g. less material invest andmaintenance) technical products, which can also combine high efficiency with aesthetics borrowed fromnature [54]. In this way, plant-inspired materials systems and technologies may not only help to reduce theCO2 footprint but lead to novel smart solutions being of particular interest in soft robotics and architecture[54, 60].
Current and future challenges
Until recently, plant-inspired soft robots and other motile systems typically used motion and/or actuation
patterns based on the form-structure-function relationships that cause motion in the model plants.
Examples include plantoid growing robots inspired by root growth [12, 60], SMA robotic searcher twigs[61], cellular actuators [54], façade-shading systems flectofin and flectofold [54, 55], and various types ofartificial Venus flytraps [62]. Despite their impressive functionality, these examples were largely produced
and actuated by conventional technical materials and methods (e.g. plantoid: additive manufacturing;robotic searchers: shape memory alloys; cellular actuator and flectofin/flectofold: hydraulically or pneumatic
actuated compound materials; AVTs: various technical materials). To use the full potential offered by motile
plant structures inspiration should be taken also from the materials systems building the underlying
structures that allow for their complex, highly robust and resilient movements. This transfer is still in its
infancy, but recent studies using osmotically/hygroscopically actuated materials systems with (hierarchical)
structuring inspired by twining tendrils [63] or pine cone scales [64] impressively prove the potential of suchapproaches. They allow for complex multi-phase movement patterns combined with considerable
mechanical robustness of the motile structures. A major challenge for achieving complex andhigher-dimensional shape changes at an acceptably short time range (< minutes) in macroscopic passive
hydraulically actuated materials systems as used for soft robots or architectural elements (>10 cm) is theporoelastic time scale [53, 65]. To meet this challenge, flow rate depending motion speed has to be markedly
improved, which could be achieved by structural speed boost mechanisms [53, 55], and long-term
performance degradation of (most) hygroscopic materials must be addressed [65]. Today, plant inspired
motile systems nearly exclusively use inspiration by nastic plant movements, i.e. movements
pre-programmed in the materials systems and performing always in the same way after stimulation. This isoften an advantage in technical applications [54], but represents only a minor part of the variety of plantmovements. Of particular interest are tropistic movements (as e.g. chemo-, geo-, photo-, thermo-,
thigmotropisms), which depend on the direction and (often) intensity of the triggering stimulus [53].
Tropistic movements are currently very rarely transferred in bioinspired applications [61, 66].

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Figure 5. Examples of plant-inspired soft robots and architectural motile systems showing motion and/or actuation patterns
inspired by the form-structure-function relationships of plants. (A)–(C): Façade-shading systems flectofold (A) and the biologicalrole model water-trap plant (Aldrovanda vesiculosa) which traps close by motion-amplification caused by bending of the leaf
mid-rib, shown in open (B) and closed state (C). (D), (E): Plantoid growing robot (D) inspired by the motion principles ofgrowing roots (here: root system of a cotton plant Gossypium sp.) (E). (F), (G): Robot tendril using SMA searcher to braid with aparallel tendril (F) inspired by intertwining searcher twigs of lianas (here: Dutchmans pipe, Aristolochia macrophylla) (G).
(H)–(J): Pneumatically actuated artificial Venus flytrap (H) combining motion principles of the Venus flytrap (Dionaea
muscipula), which traps close by snap buckling of the two leaf halves, shown in open (I) and closed state (J), and of the water-trap
plant (Aldrovanda vesiculosa) (B) and (C). (D) courtesy of Barbara Mazzolai, (E) wikimedia commons/public domain,(F) Reproduced from [61]. CC BY 4.0.

Figure 6. Examples of plant-inspired soft robots and architectural motile systems using materials systems and actuation modes
inspired by plant models. (A), (B): Bioinspired artificial tendrils using osmotically actuated materials systems for twining arounda support (A) and the twining tendrils of the passion flower plant (Passiflora coccinea) (B) representing a biological role model.
(A) Reproduced from [63]. CC BY 4.0. (C), (D): 4D-printed hygroscopically actuated scales for building envelops and roofs (C),and a seed cone (D) and seed cone scales from biological concept generator pine (Pinus wallichiana). Reproduced withpermission from [64].

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Advances in science and technology to meet challenges
Novel sophisticated methods for quantitatively analyzing and simulating the form-structurefunction-relation on various hierarchical levels in plant role models and plant-inspired technical products
were developed and accessible since the 1990s. Despite the fact that these methods, such as magnetic
resonance imaging, confocal laser microscopy and environmental electron microscopy, provide new andfascinating insights into the hierarchical structuring and functioning of still ‘living’ biological structures, andeven in 3D to a degree of detail that was previously hardly imaginable, such as micro-computed tomography,
atomic force microscopy and x-ray diffraction (via beamlines) [55–57], multiscale mechanics and otherfunctions as well as the structure-function relationship of plant models are (often) not yet sufficiently
understood [67]. This holds especially true on the mesoscale, i.e. the size range between the higher
micrometer- and the lower millimeter-range, which is of considerable interest for bioinspired motile
structures. For this size range not only improved instruments for structural and mechanical analyses aredesirable, but also better scale overarching simulation tools. For the transfer of plant-inspired concepts into
technical applications new production methods, as e.g. 3D/4D-additive micro-manufacturing,
3D-braiding-pultrusion and laser spinning, enable for the first time the transfer of many outstanding
properties of the biological role models into biomimetic products for reasonable costs. They allow to
produce—like nature—complex materials systems and structures from small to big and to combine different
hierarchical levels. Here a more pronounced transfer of the hierarchical structuring and an increased
functionalization of the interfaces may help for a more sophisticated transfer. To make the best possible useof the inspiration of plant models for moving technical systems, also the materials used are of utmost
importance. Many of the demonstrators developed today use materials (systems) like hydrogels, shapememory alloys, liquid crystalline elastomers, ionic polymer metal composites or DEs [57, 60, 62], which arevery helpful to build proof-of-concept demonstrators but often lack sufficient long-term performance andstability and/or are too expensive for industrial application. Therefore, in addition to a further improvement
in analyzing and simulation methods (especially in the meso-length scale) specifically novel more durable
and in ideal case sustainable actuating materials are highly desirable.
Concluding remarks
Especially during the last ten years plant-inspiration for motile technical structures has become more andmore visible and accepted. I am optimistic that the progress in science technology needed to address theabove mentioned challenges will take place within the next decade. However, in addition to technicaldemands necessary for tapping the full potential plants offer for soft robotics and green architecture, there
exists an increasingly urgent science policy problem: the number of organismic botanists being able toperform the necessary plant studies is constantly decreasing since the 1970s. The major reason is theincreasing dominance of molecular biology in life sciences. This not only caused a decreasing interest of
students in organismic biology but also an ongoing disappearance of the corresponding professorships.
Keeping in mind the potential and increasing importance of organismic plant biology for biomimetics andfor more sustainable future technologies this development represents probably the major thread and should
be stopped.

Acknowledgments
This project has received funding from the European Union’s Horizon 2020 Research and Innovation
Programme under Grant Agreement No. 824074, and from the Deutsche Forschungsgemeinschaft (DFG,
German Research Foundation) under Germany’s Excellence Strategy—EXC-2193/1—390951807. The author
thanks especially Falk Esser, Linnea Hesse, Simon Poppinga, Olga Speck and Marc Thielen but also manyother colleagues of the Excellence Cluster livMatS and the FET-EU-project GrowBot for helpful discussions.

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6. Sustainably grown: the underdog robots of the future
Stoyan K Smoukov
Active and Intelligent Materials Laboratory, Queen Mary University of London, London E1 4NS, United
Kingdom
StatusAutomata have captured people’s imagination for millennia. From Ctesibius’ water clock and moving owl
more than two centuries B.C., recent integration with electronics and independent high-density powersources has produced today’s mobile robots. These including rescue robots resembling dogs, snakes, andother animals. In humanoids, the last two decades’ exponential developments have eclipsed the 2002–2004
humanoid RoboCup where just standing in place and kicking a ball was considered the top achievement. The
recent demos by Boston Dynamics [68] of robots rebalancing after being pushed, as well as synchronized
dancing skills, show the goal of a RoboCup team of robots beating the human world champion team by 2050
by FIFA rules is very much on track.
It is hard to imagine current approaches are lacking somewhere, yet they will not be applicable to themajority of robots in the near future. We are on the verge of two new transitions that will transform robotics.
One is already under way—the miniaturization of robots, to the point where invisible, microscopic robots
could be around us and inside us, performing monitoring or even life-saving functions. We have seen
systematic bio-inspired efforts to create microbe-like, microscopic robots. The trend has parallels withminiaturization in the electronics industry, where exponentially smaller and more energy efficient units havebeen produced each generation. To put this statement in context, examples already include magnetic
microswimmer robots, employing bacterial modes of locomotion, which are biocompatible, potentially
ready for integration within our bodies. They require lithography to create clever microscopic screw-type
structures [69], enough to produce the cork-screw swimming movement. Such micro-robots haveencapsulated, picked, and delivered cells, protecting them from shear forces in fluids [70], while others havecaptured non-motile sperm, propelled them, and ultimately fertilized an egg [71]. We explore how suchdevelopments in micro-robots will change our world in the relatively near future.
The second trend is bottom-up robotics, growing robots from a solution medium, as if they
were bacteria. This field is emerging at the intersection of a number of disciplines, discussed below. An
overarching common theme is the creation of artificial life from a non-biological starting
point.
Current and future challenges
Sustainability and energy efficiency are front-and-center issues as robotics becomes more useful, more
affordable, and therefore more ubiquitous. This is especially true of microscopic robots that would be too
small and cheap to collect and recycle traditionally. All current microelectronics and most micro-robots rely
heavily on lithography for their manufacturing. This top-down method, though extremely precise, is rather
wasteful. For highly integrated chips, a 20 g chip requires 1.7 kg of materials inputs [72]. Bottom-up
sustainable approaches can mitigate/eliminate such waste.
E.g. inspired by plant roots, a robot created an embedded ‘root’ system building a tube around a 3D
printing head that also doubled as a burrowing tip [73]. This creative additive strategy may greatly decrease
the environmental impact and increase the versatility of architecture of embedded tube networks down tomillimeters. New physical principles and interactions between building components are needed, however, foreffecting growth of robots on the micro- and nanoscale to parallel that in biological cells and cellularcomponents. The aim would be to ‘grow’ robots at the same cost as plants and bacteria, with a similar
end-of-life decomposition cycle.
As micro-robots get smarter, a natural impulse is to integrate them with the electronics which we
associate with computation. Smarter micro-robots could greatly enhance the field of electroceuticals [74], e.g.
with their ability to relocate to different nerves and sense/deliver the right stimuli. It is also worth keeping in
mind that in nature the most energy efficient computation devices, our brains, run on ionics, not electronics.
Since 2007, huge gains in the field of ionic diodes [75] promise the creation of ionic logic and computation.
Creating artificial life is another blue sky challenge that may be achieved within the lifetimes of somepresent readers. On the small scale numerous challenges include how to harvest energy and integrate powersystems, defining shape, enabling locomotion, environmental sensing, computation, enabling division, andeventually reproduction, heredity, and evolution. In this respect the goals of engineering robotics on the
microscale overlap with those of synthetic biology in its purest form. In the next section we show significant
progress in almost all the above areas starting from abiotic compounds.
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Advances in science and technology to meet challenges
The smallest articulated swimmer (just <1 µm) is limited not only by the expense of lithography, but also by
the inadequacy of simply miniaturizing large structures. New principles needed for movement at smaller
length scales also afford simpler designs. Understanding self-assembly and phase behaviors of small
molecules would let us grow them as plants and animals grow in nature, from nutrient media using internal
programmed mechanisms. Materials science and robotics are currently in a stage of development of learningfrom life at those scales [76].
The discovery of artificial morphogenesis [77] from cooling, has allowed spherical oil droplets totransform in both sizes [78] and into shaped polymer particles [79]. Phase transitions yield regular 3D(icosahedra and octahedra) and quasi-2D geometric shapes (hexagons, pentagons, rhomboids, triangles,
trapezoids and rods). Only two chemical components are needed besides water, to grow such shapes, andremarkably only two components also for producing flagellated active swimmers, which can be recharged
from fluctuations in the environment [80]. Further functional integration in synthetic biology would let us
mimic cells with minimal number of components [81].
A combinatorial approach to multifunctional polymers has recently removed the unpredictability ofincluding extra functions in single molecules by interpenetrating multiple phases with their separate
functions. Both simultaneous synthesis and sequential interpenetration are possible [82]. Combining ionicactuation and shape memory has achieved programmable movement [83], supercapacitor energy storage[84], and self-sensing muscles [85]. All these techniques are compatible with efforts under way to combine
multi-functionality with bottom-up shaped polymer particles, to grow swimming, self-sensing,programmable and autonomous polymer robots. SH is being developed for materials to drive energy
harvesting and storage in the next generation of micro-robots [86].
Peptide amphiphiles are now assembling gels and tissues with biological signaling and nanofiber
materials with state-of-the-art tunable functionality. Recent structures with both covalent and non-covalentinteractions expand greatly the ability for tunability, responsiveness and repair, as well as dynamic functional
assemblies [87]. Sequence-defined polymers are aiming to play the role of proteins in new assembly andnano-robotic systems. Progress is being made in error-free sequence synthesis, reading sequences, and also
developing the potential for repair and the creation of catalytically active analogues of enzymes [88].
Concluding remarks
The drive of micro-robotics towards artificial life is both fundamental and practical. Constructing a living
system would be the most concrete possible answer to the Origin of Life, while also exploring minimum
requirements and expanding the conditions under which it could thrive. Practically, a population of
micro-robots could be persistently maintained under the right circumstances, though individuals die anddecompose, consistent with the goals of sustainability.
Growing invisible microscopic robots bottom-up is the convergent goal of several different fields—fromself-assembly of responsive materials, to bottom-up synthetic biology [89], to physics and chemistry of active
matter. They all aim at reproducing aspects of life, both for understanding life’s mystery, and re-creating life
‘from scratch’, as ‘doing’ is the ultimate form of ‘understanding’. Reproduction in life is also the ultimate formof self-repair—with the promise of improvement and adaptation from generation to generation.

Acknowledgment
Acknowledging funding from the UK EPSRC fellowship (EP/R028915/1).

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7. Wood and cellulose composites for material optimisation
Ingo Burgert1,2, Tobias Keplinger1,2 and Gilberto De Freitas Siqueira2
Wood Materials Science, Institute for Building Materials, ETH Zurich, 8093 Zurich, Switzerland
2
Cellulose and Wood Materials Laboratory, Empa, Swiss Federal Laboratories for Materials Science andTechnology, 8600 Dübendorf, Switzerland
1

Status
The hierarchical structure and embedded functionality within plant cell walls equip even dead plant tissues
with the capability to function as sensors and actuators. This makes plant organs and plant components
excellent role models and building blocks for composite materials and systems with autonomous behavior
for soft robotics applications.
In particular, the specific control of cellulose fibril orientation is a powerful tool as it allows for adjusting
the composites stiffness and anisotropy and predetermines the pattern and magnitude of deformation andmovement [90]. In this regard, the remarkable bending or torsional movements of pine cone scales and awns
are excellent examples. Such bilayer deformation mechanisms can be easily transferred to bioinspired
technical applications via the combination of thin wood layers with different fiber orientation utilizing theanisotropic swelling and shrinkage of the wood layers [91].
An alternative approach to develop cellulose composites for soft robotics applications is to extract
anisotropic cellulose nanofibrils (NFCs) or nanocrystalss (CNCs) by disassembly of plant cell walls and use
them as reinforcing fibrous phase in hydrogels or hydrophobic matrices for the adjustment of theirmechanical performance and deformation behavior [92]. By controlling the cellulose building blocksalignment, not only stiffness can be tailored, but also mechanical anisotropy can be implemented andcontrolled [93]. Likewise bioinspired wooden bilayer structures, hydrogel composites can perform
predetermined shape changes but with faster response times and larger deformability.
In addition to ‘bottom up’ nanocellulose assembly processes, increasing research activities follow a ‘top
down approach’, which retains the beneficial hierarchical wood structure and cellulose directionality, butenhances deformability due to softening modification treatments. In this way, hierarchical cellulose scaffolds
are produced, in which embedded responsive polymers and hydrogels provide soft robotics functionality[94, 95].
Current and future challenges
A major challenge of bottom-up processes, utilizing cellulose NFCs or cellulose CNCs as reinforcing phases
in hydrogels and polymer matrices, are their energy intense disassembly and reassembly processes. These arealso the limiting factors in reaching larger dimensions. However, great progress has been made by additive
manufacturing techniques like 3D- and 4D-printing of cellulose-based composites, which allow the design ofsophisticated structures with potential application in soft robotics [97]. The development of CNC/CNF
containing inks with optimized properties for both, the extrusion process and the final state remains
challenging, because the required shear thinning properties during extrusion restrain the nanocellulose ratio
in the ink. Furthermore, in order to retain the printed filament dimensions of the final element underambient conditions, the structures need to be freeze-dried. This restricts sample size and the ice crystal
formation partly spoils the cellulose nanoparticles alignment achieved during the extrusion process. Main
advantages, however, are the possibility to combine the cellulose building blocks with various polymer
matrices and monomers, to control their degree of alignment in the final element due to shear andextensional forces upon printing and the freedom to design customized structures with relatively complex
architectures.
Top-down approaches that utilize the structural hierarchy of dead biological tissues like wood for
actuation and movements have less constraints regarding scaling but possess other limitations. The
activation of rather rigid wood structures requires generation of high forces, which necessitate theinteraction of cell walls with water. Volume changes of modifying agents, for instance of embedded
thermo-responsive polymers, do not result in stresses being capable of sufficiently deforming the unmodified
wood structure. Hence, without an additional functionalization or modification step only humidity changes
are a sufficient stimulus for wood actuation, which certainly limits their applicability in the field of robotics.
Moreover, the slow sorption processes result in long response times and therefore, only comparably thinbi-layer elements achieve reasonable actuation times.
A common limitation that can arise for both, bottom-up and top-down approaches is the limited
repeatability of movements. When polysaccharides or proteins are used as building blocks, the systems willshow viscoelastic behavior with creep and/or relaxation during actuation and movement. Carrying own
weight or manipulating units with a certain mass may impede the infinite repeatability of robotic operations.
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Figure 7. (a) A pine cone cut along its longitudinal axis, with one half wet and one half dry (mirrored in the image); drawing of
the bilayer structure of the scale and the cellulose fibril orientations in the cell walls [90] reprinted with permission of The Royal
Soc.. (b) Bioinspired wooden bilayer with different fiber orientation actuated by humidity change. Reproduced from [91].
CC BY 4.0. (c) In situ formation of PNIPAM hydrogel in the lumina of wood cells for wood materials with embedded temperature
responsivity. [96] John Wiley & Sons. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Figure 8. (a) Wood hydrogel bent in two directions can recover its original shape. [95] John Wiley & Sons. © 2018 WILEY-VCH
Verlag GmbH & Co. KGaA, Weinheim. (b) Anisotropic swelling of a 3D printed CNC-PNIPAM hydrogel results in curling andbending of the structure. (c) Light responsiveness of a printed CNC composite with shape change after illumination. [101] John
Wiley & Sons. © 2020 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Moreover, the natural variability of bio-sourced building blocks or structures can be a severe challenge as
they hinder a precise prediction of the designated movement.
Advances in science and technology to meet challenges
For bottom-up approaches, great progress in controlling the directionality of cellulose building blocks and afeasible upscaling has been made by flow-assisted organization of CNFs into macroscale fibers [98]. Suchfibers could be used for reinforcing elements of hydrogels to reach larger dimensions in soft robotics
applications. Additionally, it needs further advances in 3D-printing techniques and ink properties finetuning to better match requirements for extrusion and the printed product, in order to enable moresophisticated cellulose-based systems. Importantly, 3D-printers still have to become more versatile to process
inks with a wide variety of composition. The major limitation that printed hydrogel actuators need to be kept
in humid environments or freeze/supercritically dried to avoid shrinkage might be tackled with recent
progress in solvent exchange processes or freeze-thawing-drying at ambient pressure. The latter allows for
scalable fabrication of highly porous cellulose-based foams [99], but might be also applicable to drying of 3D
printed inks, upon further adjustment.
The actuation of wood-based or wood-derived elements could be accelerated by chemical modifications
to speed-up the water uptake or release. Additionally, geometric adaptations that reduce sample volume inactuating segments are possible. However, based on the abovementioned challenges, it remains rather
unlikely that hydro-actuated wood elements, although being able to perform autonomous movements,
become a dominating material in soft robotics applications.
Potentially, new opportunities arise from concepts that use delignified wood structures, in which thebeneficial cellulose orientation is retained. The removal of lignin strongly reduces the transverse rigidity ofcell walls, making thin wood sheets more flexible without losing elastic anisotropy [94, 95, 100]. Such
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cellulose composites allow for a higher cellulose volume fraction and relatively simple upscaling techniques
compared to the disassembled counterparts.
Beyond actuation of entire elements, these cellulose structures may also function as hierarchical scaffoldsof large porosity in which soft stimuli responsive hydrogels can be embedded for their actuation as
switchable membranes in cellulose-based compartments [96].
Concluding remarks
Cellulose composites are likely to play a decisive role in material optimization for soft robotics applications in
the future. Cellulose can act as a reinforcing phase for hydrogels and other matrices (as cellulose scaffold oras cellulose building blocks (NFC/CNC)), which allows adjusting, increasing and controlling the stiffnessand elastic anisotropy of the composites. Further developments in bottom-up 3D-printing technologies will
enhance this process, but certain challenges still have to be addressed. The use of cellulose scaffolds in a
top-down approach may become an important alternative, but it needs more research activities in this field
to identify its true potential.
In the future, aspects of materials selection and functionalization as well as materials decomposition after
use phase need to become more relevant in order to implement a better composites recyclability andsustainability. Using cellulose, a renewable and CO2 storing resource, certainly provides benefits, butfunctionalization treatments and mixture with less sustainable materials can easily spoil the natural merit.

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8. Shape-memory polymers and actuators for soft robotics
Andreas Lendlein
Institute of Active Polymers, Helmholtz-Zentrum Hereon, Teltow, Germany
Institute of Chemistry, University of Potsdam, Potsdam, Germany
StatusShape-memory polymers (SMP) are active materials capable to perform shape-shifts on demand [102].
When exposed to heat, SMP can revert a mechanical deformation, which was temporarily stabilized bysolidification of a switching phase. Such phase is formed by chain segments, which are linked to net-points
determining the permanent shape of the material. The switching segments are flexible at high temperature
and allow the deformation of the polymer as they can change from a random coil to an oriented, stretchedconformation. Upon release of the external stress at this high temperature, the original, permanent shape isrecovered driven by an entropy gain. If the SMP is cooled below the thermal transition T trans associated to theswitching phase while keeping it deformed, the switching segments lose their conformational flexibility andfix in this way a temporary shape, which is obtained after releasing the external stress. This temporary shapestays unchanged until the temperature exceeds a switching temperature T sw . It can be determined inthermomechanical tests and depends on the temperature T deform , at which the SMP was deformed before.
Deformations between the temporary shape and the permanent shape can be quite high given the nature ofelastic deformability of polymer networks. Elongations larger than 1000% have been successfully realized.
This classical thermally induced shape-memory effect (SME) of polymers is a one-way effect. Once thepermanent shape has been recovered the polymer needs to be programmed again.
This limitation was overcome by the discovery of shape-memory polymer actuators (SMPA), which areable to reversibly switch between two shapes controlled by temperature [103, 104]. The reversible movementof such materials is based on the crystallization induced elongation of actuation units consisting of chain
segments oriented along the deformation direction and melting induced contraction by entropy-driven
recoiling. While one-way SMP can serve as thermomechanical energy storage systems, SMPA can be applied
as artificial muscles in soft robots.
Current and future challenges
The one-way SME of polymers can be applied in macroscopic robotic systems such as space vehicles.
Self-unfolding sun sails or self-expanding porous tires are examples for features which have been successfully
demonstrated using SMP as thermomechanical energy storage systems. The expansion of a folded orcompressed device is also of interest for minimally invasive surgery, where a spacious implant needs to be
implanted through a small incision [107]. Once the relevant position for the procedure has been reached, e.g.
by use of a catheter, the implant should expand to its application relevant spacious shape driven by therelease of the stored mechanical energy. A typical requirement in such type of applications is the capability ofthe materials to perform complex shape-changes. This challenge has been initially addressed by triple-shapepolymers, which can perform two subsequent shape-changes while the temperature is increased. Meanwhile,
several shape changes can be programmed in one material in terms of a multi-shape effect [108]. Even
thermosensitive quadruple-shape hydrogels could be realized. Research in this area is going on and newrecords in the number of shape changes as well as technologies to change the sequence of shape-changes canbe expected. The latter has been addressed exemplarily by a multi-material system, in which different ways totransfer heat in the material system led to variations, which part of the devices moved first [106]. Thesesystems are in principle performing a sequence of several one-way SMEs, which are triggered at different
temperature levels. In this way the stored mechanical energy can be release in portions.
SMPA are highly relevant for soft robotics as artificial muscles [109]. They have been explored as active
material in robotic hands and grippers. Textiles for soft robotic skin applications are being developed andcould be further advanced to act as an exoskeleton. SMPA are thermally-controlled and (re)programmablewith regard to the geometry of the reversible shape change, such as stretching, bending or twisting. This(re)programmability is enabled by a second set of crystallizable domains, which are forming crystallites
associated to melting temperatures (T m ), which are higher than the Tm range related to the actuating units.
These crystalline domains form a scaffold structure within the SMPA, which spans the oriented actuating
segments along the direction of the macroscopic movement. The incorporation of two different actuating
units with distinct temperature ranges of their thermal transitions results in non-continuously moving
actuators, which are a first step towards more complex shape-shifting geometries.
The application of SMP and SMPA materials in robotic systems [110] requires adequate
processing/programming technologies including digital fabrication methods [111, 112] and suitableconnectivity to controller systems, which could be electronic or optical systems.
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Figure 9. (a) Thermally induced one way shape-memory effect of a polymer. [105] John Wiley & Sons. © 2005 WILEY-VCH
Verlag GmbH & Co. KGaA, Weinheim. (b) Reprogrammable shape-memory polymer actuator. [103] John Wiley & Sons. © 2013
WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. (c) Adjustable sequence of two shape changes in a multimaterial system
exhibiting a triple shape effect. [106] John Wiley & Sons. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Advances in science and technology to meet challenges
Recent progress in one-way SMP/temperature-memory fiber technology demonstrates the relevance asthermomechanical energy storage systems. Programming is the process to load the nanocomposite fibers
containing graphene oxide nanosheets by twisting [113]. The stored energy is released when thetwisted fiber is heated. Such thermosensitive twisted fibers could serve as microengines driving small softs
robots.
Living machines, especially those working autonomously by harvesting energy from the environmentand being controlled by stimuli provided by nature, are a relevant technology field for SMPA. An example
illustrating this potential are external shading lamella for house facades, which close during intense sunlightperiod driven by heating and open in the evening automatically as temperature decreases. The challenge hereis the scalability of the SMPA technology, which can be addressed by using commodity semi-crystalline(co)polymers or blends of these in combination with postprocessing crosslinking [104]. Longterm stability isessential for such applications and could be reached by integrating additional functions such as SH [114] orantioxidant capabilities of the SMPAs. SMPA technology could also be used to build a heat engine harvestingenergy from cyclic day/night temperature changes. Formation of SMPA-based (nano)composites could also
lead to magneto-sensitive or electrically conductive artificial muscles. Coupling the functions of indirect
heating and thermally-controlled actuation would result in actuators, which could be controlled byalternating magnetic fields [115, 116] or by electrical current. Electrically-controlled artificial muscle fibers
can be integrated in textiles and in that way form a platform for soft textile robots. In general, there is a needfor faster actuation, lower energy consumption and control by alternative stimuli, especially low-intensity
light would be of great interest. Finally, medical applications of soft robots are demanding multifunctional
SMPA, which are cell-/tissue- compatible and potentially degradable. Recent advances in shape-memory
sheet actuators involved the demonstration of programmable bioinstructivity directing stem celldifferentiation into the osteogenic lineage [117]. Health technologies supporting elderly people by soft
robots is another promising field.
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Figure 10. (a) SMPA based shading lamellas (b) heat engine driven by a concertina-shaped SMPA drive element. (a), (b)Reproduced with permission from [104]. (c) Reversible noncontinuous twisting actuation. Reprinted with permission from[118]. © 2017, American Chemical Society. (d) SMP fibers for rotating microengines (figure on the right). From [113]. Reprinted
with permission from AAAS.

Concluding remarks
Artifical muscles and efficient energy storage systems are key components of soft robots. SMPA and SMP are
therefore highly relevant active materials for the field as they can be produced based on commodity
polymers, their processability by established methods such as extrusion or injection moulding has been
demonstrated and they provide (re)programmability. Complex structures including multi material systems
can be designed and fabricated by digital technologies, which allow fast prototyping and individualization.
Future design principles for such robots might also be inspired by nature, especially by principles found in
the plant kingdom [119]. Progress is expected towards multifunctionality as well as system compatibility forvarious controller technologies. SMPA are also attractive candidate materials with regard to sustainability as
renewable starting materials are available and SMPA can be driven by temperature changes in the naturalenvironment. Healthcare technologies, autonomous systems for agriculture or aerospace as well as living
machines including adaptive buildings are promising application areas for SMPA based soft robots.

Acknowledgments
This work was financially supported by the Helmholtz Association through programme-oriented funding
and received funding from the European Union’s Horizon 2020 research and innovation program underGrant Agreement No. 824074 (GrowBot).

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9. Modeling soft robots
Felix Vanneste, Olivier Goury and Christian Duriez
University of Lille, Inria, CNRS, Centrale Lille, UMR 9189 CRIStAL, F-59000 Lille, France
StatusIn soft robotics, the behavior of the robot in deformation is inherently dependent on the type of material thatis used. Consequently, we limit the focus of this perspective paper to modeling approaches that include
constitutive laws of materials.
Solid body deformation laws from continuum mechanics include the material properties and are an
excellent basis for accurate modeling of the soft robots. Numerical methods are routinely used in engineering
to integrate these equations and model deformable structures. In civil engineering for example, the finite
element method is used to assess structure strength and stability. But in these types of applications, there isno special concern of having interactive simulations, running at high frame rate. A first challenge inmodeling soft robots was to make numerical methods compatible with real-time simulation which isnecessary for control.
Several approaches were proposed to solve this performance problem, among which we can cite:• Reduced parametrization: typically used for slender robots, this allows to describe the motion with few
degrees of freedom along one space direction only. Examples include Cosserat or Kirchhoff models [123].
• Model Order Reduction: applied to finite element models, it allows to represent the degrees of freedom in a
reduced yet accurate surrogate model, which allows for interactive simulations, and can be used for robots
with any geometry [120].
• Static condensation: used on a coarse FE mesh to obtain the compliance coupling between actuators andeffectors, it can lead to direct and inverse kinematic models [121, 124].
• Automatic derivation: in [125], the gradient of a sensing objective can be computed with respect to design
variables, allowing for an automatic optimization of sensors placement. This is an alternative approach forinverting models, for design and control.
• Exploitation of high-performance computing to speed up the computation, using clusters or GPUs.
Soft robots are naturally more suited to interact with their environment. Consequently, an important aspect
is to model these interactions and in particular contacts, in an interactive manner. This was done in real-timeusing an inverse model and a QP-solver in [121]. Numerical models of deformation can also be used forsensor data fusion [126]. For feedback control, these mechanical models can be used in closed-loop to adapt
to sensors readings dynamically [127].
Current and future challenges
There is an obvious need to account for constitutive laws that are more complex than (hyper-)elasticity.
Plasticity [130] or fatigue laws received little attention in the community but are key to predict the reliabilityof soft robots. An issue related to that is the problem of mixing different materials in the same robot to create
specific behaviors. Then, regarding the inclusion of various kind of actuation, multiphysics model are needed
to couple the mechanics of the robot with heat transfer for shape-memory alloy, electrical field [131] forelectro-active polymers, chemical for ionic polymers, or pressure for pneumatic actuators. Regarding
underwater robots, of flying robots, the mechanics must be coupled with fluid-flow simulations [132].
Then, for fitting these complex models to real-life, work remains to be done in the field of identification
to find correct physical parameters in an efficient and accurate manner.
Dealing with complex contact situations must be addressed, since contacts play an important role
especially in soft robots but can be a computational deadlock, when robots have complex geometries or
induce self-collisions, and can lead to numerical instabilities. A first investigation was made in [133].
Regarding the use of these models to train AI algorithms or for design optimization remains an open
question since these applications have their own challenges. When using the model to train a machinelearning algorithm for control, it is still difficult to make sure the training is done on sufficient data when
considering interactions with the environment: will the trained control be able to handle new contacts?
For design, many parameters are involved, such as shape, constitutive law, actuators positions, etc…
Using a simulation of the robot is very useful. When optimizing with simulations, a reward function isdefined and has often to be a compromise between several objectives that have to be weighted. Finding ageneric method to define those reward functions is still an open question. Another difficulty occurs when
considering parameter with respect to which it is hard to define the derivative of an objective function. Theseissues, challenges and opportunities of simulation for robotics were identified recently in [134].
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Figure 11. (1) Position comparison between a full order model (FOM) with fine and coarse mesh and a reduced order model(ROM) of a tentacle [120], (2) soft robot controlling the orientation of a plastic cup actuated online using the output of thesimulation handling contacts in real-time [121], (3) dynamic control of a tentacle tip along a trajectory [122].

Figure 12. (1) Top: sensor fusion approach for force and shape estimation using FEM [126], bottom: sensor design for
proprioceptive soft robots. Reproduced with permission from [125]. (2) simulation and use of mesostructured material to create
anisotropic behavior [128] (3) use of an evolutionary optimization algorithm to do shape optimization [129].

Advances in science and technology to meet challenges
There is still a lot of progress to be made to further improve performance, especially for dynamic
deformation models. For control, simulations must be fast, in fact, faster than real time for predictive
control. The addition of multiphysics approaches [131, 132] in the numerical models mentioned above will
be important when one wants to create complex designs but will also increase the amount of computations.
The issue of reducing computation time and reducing model orders are therefore central [120, 133, 135].
Model-based and data-based approaches are not necessarily opposed. One could imagine scenarios
where machine learning techniques are used to build a part of the predictive model, from data taken from therobot or its environment and from simulated data. This data-based model could also potentially besimulated in interaction with models based on physics equations. We can imagine methods for
identification, calibration or even on-line re-calibration of models from the data. There are clearly importantscientific advances to be made on merging the different approaches. It seems to us a pity to systematically
oppose methods by a naïve dichotomy between ‘model-based’ and ‘model-free’.
In order to meet the challenges mentioned above, it is necessary for the community to have a sustainedcommitment to software development and multidisciplinary training. Indeed, the numerical models
mentioned above require skills and knowledge in numerical mechanics that are sometimes far from thebasics of modeling in robotics. We believe that the development and validation of open source simulation
platforms should be encouraged in order to advance the whole soft-robotics community on this subject.
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This is what we tried to develop with the SOFA framework and the plugins dedicated to soft robots. Thesesimulation tools need to be easier to use and more accessible to most users and to allow rapid virtual
prototyping.
Beyond pure simulation of robot behavior, more advanced geometric tools will be needed to parametrize
the geometry of soft robots. Indeed, this point is essential to be able to optimize the shape of the soft robots.
The multi-scale aspects, so present in nature from which soft-robotics draws its inspiration, will also be an
obvious direction for the modeling aspects.
Concluding remarks
Numerical models based on continuum mechanics are quite generic, and account well for material
properties. They are suitable for the design and control of soft robots. Computation time can be fast enoughfor robotic applications with real-time constraints. We believe that this is one of the paths to follow for themodeling of soft robots, in particular to accompany research towards more and more sophisticated designs
based on multiphysics. Collision avoidance is outdated in the context of soft robots, the modeling approach
will focus on collision permission and use.
The development of numerical models based on deformable body physics allows to take into account the
specificity of soft robots. Integrating these models in an efficient and open toolbox should contribute to abroader convergence within the (rigid and soft) robotics community.

Acknowledgments
Projects of the research team DEFROST is financed by the French National Agency for Research (ANR), andby the European Union through the European Regional Development Fund (ERDF).

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10. Realtime mechanical impedance control in soft robots for information gain andefficient control
Thrishantha Nanayakkara
Dyson School of Design Engineering, Imperial College London, United Kingdom
StatusThere are two main phenomena where mechanical impedance control contributes to improve efficiency ofrealtime interactions with the world:
Realtime intrinsic conditioning to assist force/motion control
A bicycle rider would come off the seat and ride with bent knees on a bumpy terrain. The mechanical
impedance conditioning at the knee helps to filter task irrelevant noise from the terrain. Similarly, in manyother interaction tasks, biological counterparts condition the body while doing motion and force control.
For instance, in a task of estimating the depth of a hard nodule in a soft tissue, participants show handmuscle co-contraction with statistical patterns unique to the depth of the nodule [136]. Independent robotic
finger experiments show that this stiffness regulation helps to shape the likelihood function in a Bayesiantissue parameter estimation process [137]. Such stiffness conditioning works in the background whileregulating palpation force and speed of fingers [138].
Exploitation of passive dynamics in a layered control architecture
Recent mountain goat inspired robotic hoof experiments show that specific levels of compliance acrossdifferent joints in the hoof lead to a significant improvement in passive dynamic slip resistance [139]. Workdone on Rodents [140] and Cephalopods [141] show hierarchical control, where local control loops use
passive dynamics of the body to solve certain computational problems autonomously. Conditioning the bodyto exploit passive dynamics of the body plays an important role here. The reaching movements in the
Octopus is one example [142] where it sets the stiffness of the tentacle to behave like a rope being unrolled
along a straight line going through the prey.
Current and future challenges
Computational challenges
Most robotic systems require high sampling rates for stability. In contrast, biological systems tend to pay
attention to states only at strategic points. For instance, during legged locomotion, we pay closer attention at
the point of foot colliding the ground and not so much at how the leg swings forward. In the case of theOctopus unrolling the tentacle [142], it checks whether the prey is caught at the end, if the prey is not caught,
it pulls back and throws again. In addition, robotic systems still struggle to perform high bandwidth stiffness
conditioning while performing force/velocity control tasks.
Control architecture challenges
As mentioned in the previous section, the efficiency of physical interactions involving perception and action
depends on the interplay between concurrent extrinsic force/movement control and intrinsic mechanical
impedance parameter conditioning processes. I call the orchestration of these concurrent motor control
processes to be ‘behavioral lensing’ because it leads to an improved perception of task relevant states withhigher task stability. Current robotic systems face the challenge of such concurrent control due a lack ofunderstanding of how one helps the other.
Hardware challenges
All current robotic stiffness control mechanisms find it hard to match the speed and range of stiffness
achievable through muscle co-contraction in biological counterparts. In addition, force/weight ratio is amajor challenge for robotic actuators to come close to biological muscles. Coupled sensing and actuation isanother challenge that biological muscle spindles and tendons accomplish elegantly.
Advances in science and technology to meet challenges
Realtime computing in the physical body
The cochlea in the auditory system is a good example for a physical computer that solves the realtime
frequency components separation problem for audition [143]. We have found that the knee joint also solves
a similar problem of entropy reduction of contact forces during walking [144]. Progress in this area will help
to replace computer algorithms with more robust multi-purpose physical systems in the robot’s body.
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Entropy reduction through physical conditioning
The theory of contracting regions in nonlinear dynamics of physical systems [145] to reduce the entropy of
the world needs more attention. In the case of the bicycle rider, the bent knee provides such a contracting
region in the state space that reduces the uncertainty of the world. Advances in this area together with highbandwidth physical actuators will make a significant difference.
Dimensionality reduction in the state space through physical conditioning
In the case of an Octopus, throwing the tentacle to catch prey uses passive dynamics in a hyper redundant
system that unrolls along a straight line to minimize hydraulic resistance [140]. If the prey is caught, it would
make two rigid links with a joint at the middle to bring the prey to the mouth. Both throwing and fetchingstrategies reduce a multi-dimensional control problem to reduced state space control problem.
Advances in hardware
It is very important to make advances in high bandwidth high force/weight ratio actuators and soft sensors
that can be conditioned to change their bandwidth to suit the perception task. Deeper understanding of how
muscle fibers contract given low voltage signals and how sensors such as spindles and tendons function in
conjunction with actuation will provide a good basis for such bio-inspired sensors and actuators.
Self-guided physical adaptations
Still robot hardware iterations have to be done by human designers. Future advances to use a statistical
history of control action for realtime intrinsic conditioning of the physical body to self-discover permanent
physical adaptations will make ground-breaking advances in design iterations of robots especially for private
environments such as households, hotels, and offices that limit direct feedback to designers.
Concluding remarks
Conditioning the mechanical impedance parameters of the physical body serves multiple purposes such as
improving the stability of dynamic interactions, quality of perception, realtime computation to meetdeadlines imposed by an interaction task, dimensionality reduction in state space control, and efficiency of atask. Biological counterparts accomplish these through neural and physical mechanisms. Phenomena such as
stiffness control of fingers during palpation or by a tuned physical mechanism such as the goat hoof for slip
resistance are examples for physical computing solutions in addition to the direct computational
contributions from the brain. Since conditioning the physical bod too takes some time to accomplish, I argue
that long term adaptations may try to make either realtime conditioning easier or not frequently required.
From a realtime conditioning point of view, robots can benefit from high bandwidth and high force/weightratio actuators. Moreover, future control architectures that would efficiently arbitrate the concurrent
processes of intrinsic conditioning and extrinsic movement and force control will make useful advances inphysical robots interacting with the natural world. Future ability of physical robots to discover their own
physical improvements to make it easier to condition their bodies to suit task requirements or not to needfrequent conditioning at all will revolutionize approaches to design iterations of physical robots.
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Acknowledgments
This work was supported in part by the UK Engineering and Physical Sciences Research Council (EPSRC)
MOTION Grants EP/N03211X/2 and EP/N03208X/1, and EPSRC RoboPatient Grant EP/T00603X/1.

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11. Self healing soft robots
Bram Vanderborght, Joost Brancart and Seppe Terryn
Vrije Universiteit Brussel and imec, Brussels, Belgium
StatusNatural organisms have extraordinary complex bodies in which the combination of soft, compliant, stiff, andeven sometimes brittle materials incorporates an embodied intelligence that allows to move with the highest
efficiencies [146]. Their bodies are not over-dimensioned for the daily tasks they fulfil, but in unexpected,
threatening situations they can get injured. They are prone to cuts, tears, ruptures and fractures fromexternal sources or from overloading. Luckily, natural organisms have the remarkable, unique property tofeel pain and heal damage when accidents and injuries occur. The remarkable healing process starts up
autonomously and after the necessary healing time, depending on the magnitude of the damage, thefunctional properties are completely recovered. Consequently, this powerful biological healing ability allowedorganism bodies to evolve towards highly efficient designs.
Although highly inspired by organisms, soft robots in general do not have healing capacities. Theircompliant bodies allow safe human-robot interactions and make them resilient to impacts and collisions. But
their lifetime is limited due to damage caused by sharp objects or overloading, which both often occur in
unstructured, dynamic environments in which these robots will be used [147]. Traditionally, this problem isaddressed by over-dimensioning the system, making it able to withstand harmful situations, but thisapproach compromised the flexibility, the safety, as well as the efficiency of the design. Organisms and theirhighly efficient, healable bodies have inspired scientists in the last five years to impart synthetic healing
functions in soft robots [148]. They do so through manufacturing them from ‘SH polymers’, giving them thecapacity to heal from microscopic and macroscopic damage. Since the pioneering works of White et al [149],
a broad range of SH polymers has been developed, based on a variety of chemical and physical principles[150]. This has led to innovative applications, of which SH soft robotics are one of the most recent andpromising. Although this novel approach is still highly novel and challenges remain unaddressed, it has topotential to increase the lifetime of future soft robots and the recyclability, reducing maintenance andecological footprint, while permitting to optimize the design. Through the adoption of SH polymers inrobotics, this SH technology can find its way to other industries like automation, automotive andmachines.
Current and future challenges
The integration of a healing capacity is only a reliable and sustainable solution to the vulnerability of soft
robots if the healing of a damage is performed fully autonomously, without external or human interventions,which are in general cost inefficient. Autonomous healable SH polymers, able to heal macroscopic damage
without the need of a stimulus other than the formation of damage, have been introduced recently in soft
robotics [151] as well as non-autonomous SH polymers that require a stimulus, e.g. heat or light irradiation,
to perform healing [148]. There is a general trade-off between mechanical strength/stability of the polymer
network and the intensity of the healing stimulus or the healing duration [147]. This is translated into soft
robotic prototypes that can heal autonomously but have a limited force and power output due to their
hyperflexible bodies [151] and others that have a higher mechanical performance but require external
thermal or UV irradiation in order to heal [148]. In the near future, this problem can be addressed using new
generation SH polymers, in which simultaneously enhancing the mechanical and healing properties areenhanced. On a system level, the incorporation of a stimulus providing system, integrated heaters or
UV-emitters, allow to use non-autonomous SH networks with high mechanical strength and stability in asoft robot system that recover autonomously.
To react autonomously to partially or complete failure, a damage sensing capability must be included infuture SH soft robotic system. When damage occurs, the embedded damage sensing network can provide thetrigger to activate the healing procedure, prompting the whole system to rest and heal before (more) serious
damage occurs, restoring not only structural integrity by reattaching broken parts, but also restoring
complex functions like actuation and sensing. Embedded sensors for damage detection or force
measurement or state estimation as well as integrated heaters cannot compromise the flexibility of the soft
robotic system. New advances in soft sensors and flexible heaters facilitate this but they are also prone todamage and consequently, these systems need a healing capacity as well. Hence the need for development ofSH materials with additional functionalities, such as conductivity for flexible sensor or flexible ohmic heaterapplications. Finally, dedicated processing techniques for SH polymers and composites need to be developed
to manufacture the complex SH soft robotic systems.
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Figure 13. Advantages and disadvantages of soft robots, that can be addressed by introducing an autonomous damage sensing andhealing capability in the system. This can lead to further optimization of the system on an energy efficiency, economical andecological level.

Advances in science and technology to meet challenges
The requirements for SH materials, imposed by new applications in soft robotic, were summarized in areview paper by Terryn et al [147] and pushed the development of new generation SH materials thatcombine fast healing and high mechanical strength through smart polymer network design, new reversible
chemistries or though combining multiple SH mechanisms in a single network. An impressive new material
is presented by Pena-Francesch et al [152], that is able to heal large damages in seconds at 50 ◦ C and has amechanical strength of 20 MPa.
In the fast growing field of soft sensors, recently the first healable soft sensors [153] have been reported
that are composed out of SH polymers having additional electrical properties that are inherent to theirchemistry or through the addition of electrically conductive fillers to obtain piezo resistivity. Integrated in asoft robot, these SH soft sensors can be employed to measure strain, deformation, pressure, and ultimately
for structural health monitoring of the robotic part. Advances in healable flexible heaters [154] allow toincorporate the stimulus providing system directly in the material without loosing the flexibility. As the softbody in which they are integrated, these flexible sensors and heaters will be able to heal from macroscopic
damages. In addition, compounding with magnetic or photothermal fillers allow remote-controlled andlocal activation of SH processes [155], providing new methods to provide the stimulus in future soft robots.
Using multiple materials in a single design can improve the performance of soft robots and can allow newcomplex deformation modes and embodied intelligence. However, the multi-material interfaces are mostly
weak, as they rely mainly physical interactions and consequently fail at a limited number of actuation cycles.
By judicious design of the polymer network structure, the mechanical properties of SH polymers can betuned over a broad range [148]. The reversibility of the network formation permits chemical bonding acrossthe contact surface of materials with different properties allowing to achieve excellent interfacial bonding,increasing the robustness of multi-material soft robots [156]. Recently, additive manufacturing of SH
polymers [157] as well as novel processing techniques that explore the reversible nature of the network [148]offer great design freedom in the manufacturing of the future complex SH soft robots.
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Figure 14. In order to achieve autonomous healing in soft robotics, challenges in multiple subfields must be addressed, including
developing self-healing sensors for smart motion control and damage detection and self-healing electronics for stimulus andhealing control. All fields rely on and push further development in self-healing polymers.

Concluding remarks
Although the integration of healing mechanisms in soft robots is still quite novel, some impressive SH soft
robotic prototypes have been presented in academics in the last five years. These advances on the applicationlevel, reveal limitation of SH polymers and push the material development towards increasing mechanicaland healing performance and including additional functionalities. To achieve the final goal of a soft robotthat detects and heals macroscopic damage autonomously, multiple technologies like SH polymers, SH
sensors, smart motion controllers, health monitors and integrated stimulus providing devices, must be
combined in an intelligent system. The authors believe that the fast advances in the subfields, show that thisambitious objective will be achieved in the coming five years. It is however important to involve materialscientists at every stage, such that they get clear insights in the requirements and needed improvements forthe materials. A synergetic relation between all fields will result in mutual benefits.

Acknowledgments
This research is funded by the FWO-grants of Terryn (1272621N), Brancart (12W4719N) and by the EU FET
Project SHERO (828818) and EU project SMART (860108).

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12. Power sources for soft robots
Steven I Rich1, Ruiyuan Liu3, Kenjiro Fukuda1,2 and Takao Someya1,2,3
1
Thin-Film Device Laboratory, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
2
Center for Emergent Matter Science, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
3
Electrical and Electronic Engineering and Information Systems, The University of Tokyo, 7-3-1 Hongo,
Bunkyo-ku, Tokyo 113-8656, Japan
StatusAs the abilities of soft robots to sense and manipulate their environment continue to improve, the questionof how to power these systems becomes ever more critical to their practical implementation. While manylab-based devices use tethered systems to provide electricity or pressurized fluid to control these robots, one
final step to achieving wearable and autonomous soft devices is ‘cutting the cord’—endowing these machineswith their own on-board power systems to enable them to leave the nurturing womb of the laboratory, andfind their place as untethered search-and-rescue robots, assistive devices, and drug-delivery systems.
Because of the performance limitations and power constraints associated with soft actuators, however,design of soft robotic power systems presents different challenges than those associated with conventional
systems. Power sources for soft robots must balance the standard metrics of power output and lifetime withthe soft robotic considerations of flexibility and light weight, while considering other important factors likerobustness, safety, and cost, which may come at the expense of performance. Combined with the high-power
demands of many popular soft actuation systems, these trade-offs have made implementing on-board power
particularly challenging for soft robotic applications.
Accordingly, many groups have turned to consumer-available state-of-the-art rigid energy storage
devices, particularly those with high energy densities and small volumes like lithium-ion batteries forelectrically powered actuators [158] or compressed gas cylinders for pneumatic ones [159]. For componentsthat require less energy, such as sensors, lightweight and flexible power solutions (including both storage andpower generation components) have also been widely implemented. Thin film photovoltaics [160],
triboelectric nanogenerators (TENGs) [161], and wireless near-field power transmission [162] have beenused to directly power sensors. Since most soft sensors still require continuous power input in the working
state, using self-powered sensors, such as photodetectors for light [163] and nanogenerators for strain andpressure [164], can help relieve some demands on the primary battery or power supply. As power systems
continue to improve, we can expect to see untethered soft robots with smaller sizes, lighter bodies, longer
ranges, and greater functionality for many exciting applications.

Current and future challenges
Before we can achieve such soft robots, however, there remain several important challenges within thesepower systems that must be addressed. While improvements in traditional battery technologies have brought
improved lifetime and performance to many soft robots, their high rigidity and weight introduces otherchallenges, pushing soft roboticists to look toward alternative, cutting-edge flexible power solutions.
Compliant batteries or battery arrays can be achieved by decoupling the energy storage and compliant
components or by organizing energy storage units into deterministic structures (i.e. structures renderedstretchable by their geometric configuration). Similarly, supercapacitors, which have also recently achieved
high compliance and durability through the use of ultrathin materials and deterministic structures, canimprove the speed of current delivery, especially useful for fast-response actuators and thin-film based soft
electronics at low driving voltage. These systems, however, face a natural trade-off between energy density
and compliance, as structures capable of relieving strain often have a larger volume (e.g. spirals or serpentine
structures). This imposes limits on the capacity of such energy storage components, which can restrict therange or lifetime of soft robots.
To alleviate these restrictions, energy harvesting systems (systems that gather energy from theirsurroundings—such as flexible photovoltaics, TENGs, and thermoelectric generators) can supplement
energy storage components, helping to circumvent the need to charge or replace on-board batteries.
However, these advanced power systems present two new challenges: attaining sufficient power density
and sufficient compliance. The reduced energy density of compliant systems exacerbates the challenge ofmatching the energy required by a given actuator or sensor with the energy available from the power systems,
often requiring auxiliary components like power management circuits or regulators (figure 15). Coupledwith the vast range in compliance for these power sources, and additional requirements like size, discharge
speed, and energy density, these constraints can render the selection of a power source quite challenging.
Fortunately, the scaling laws of these systems, in particular the dependence of their power output on volume
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Figure 15. A comparison of the power requirements of various soft robotic technologies (represented by the shaded circles) andthe power output capabilities of various soft robotic power sources (represented by dotted lines). Although there are many
additional considerations when selecting a power source, this plot may serve as a general roadmap to match sensors and actuators
to their appropriate power sources. Abbreviations: PVs—photovoltaics, TENGs—tribooelectric nanogenerators,
TEGs—thermoelectric generators, SMAs—shape memory alloys, IPMCs—ionic polymer-metal composites, DEAs—dielectric
elastomer actuators.

(e.g. batteries) or area (e.g. solar cells), can be exploited to capitalize on the strengths of specific powersources.
Advances in science and technology to meet challenges
As power demands for soft robots push existing power sources to their extremes, further progress will require
improvements in performance and system integration. The needs of soft robotic systems (some of which are
shown in figure 15), therefore, should serve as a road map to the development of advanced soft robotic
energy sources. A fuller understanding of the mechanisms at work in these devices, as well as concomitantadvances in stretchable conductors and active materials (e.g. conjugated polymers) can help researchers todevelop soft power sources with greater performance. In addition to material architecture, creative structuraldesign can adapt existing high-performance power sources into compliant shapes (e.g. creating stretchable,
buckling power sources by mounting ultrathin photovoltaics on prestretched substrates), creating new power
storage or energy harvesting devices suitable for advanced soft robots. Furthermore, combining manydifferent power elements (e.g. energy harvesting and energy storage devices) within a single robot may help
to capitalize on each source’s advantages while minimizing its weaknesses. In particular, energy storage
devices may be needed to smooth over large variations in energy harvester output or create the large spikes in
power needed for actuation (figure 16).
A parallel strategy to facilitate the development of soft robots is to reduce the relative energy demands onthese power systems. This may mean simply advances in actuator technology in terms of efficiency, strength,
or work density, or even, as in the case of biohybrid robots (e.g. cyborg cockroaches), off-loading specificrobotic functions to the metabolisms of certain animals [165]. Alternatively, scaling up or down these robots
can improve performance by taking advantage of differences between the energy demands and relative
strengths of different actuators and the energy densities of various power sources [166]. Using non-electrical
power sources like chemical reactions, may help to power pneumatic robots as well [167].
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Figure 16. Representation of different profiles for power generation, storage and consumption. This figure demonstrates how
power storage components can be used to create uniform power output (e.g. for continuous sensing applications) from energy
harvesters with variable power generation, or create a high peak-power output (e.g. for actuation applications) from energy
harvesters with low, continuous power generation.

Since the success of untethered soft robots remains inextricably linked to their power sources, continued
work on these challenges is critical to the development of the entire field. Recent results increasing
compliance and power density have shown great promise, and simultaneous improvements in actuators andsensors will yield many exciting new robots. As these systems begin to enter the marketplace, otherconsiderations, such as mass-producibility, reusability, durability, and environmental friendliness will
become more and more important. With these efforts, we may soon face a world where soft systems form an
integral part of our everyday life.

Acknowledgments
The work shown in this section was partially supported by JSPS KAKENHI Grant Numbers JP18H05465 andJP18H05469.

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13. Plantoids and self-growing soft robots
Barbara Mazzolai
Alessio Mondini, Emanuela Del Dottore, Laura Margheri, Istituto Italiano di Tecnologia, Italy
StatusIn the last few years, plants have raised the attention as a new model for the field of bioinspired and soft
robotics [73, 168–171]. Plants are an interesting model for their high plasticity that allows them to adapt,survive under stress, and respond to changing conditions while growing [172]. In terms of technology
design, most relevant features of plants include their capability of indeterminate growing (both above andbelow soil), movements without muscles, structural materials endowed with morphological adaptation andvariable stiffness, distributed sensory system and control architecture, anchoring and attachments strategies,
intra-system and inter-system communication, and energy saving mechanisms [173].
The roots of plants have been investigated for first by researchers as model for developing autonomous
robots able to explore soil [174]. Delegated to the foraging and anchoring of plants, roots are able to move insoil by growing and adapting to the environment, avoiding obstacles, and following nutrients and water
gradients using integrated sensor units. Based on these natural features, artificial roots have been designed by
implementing a growing mechanism (i.e. a miniaturized 3D printer machine) that adds new material to thebase of the tip to push it forward into the soil, while creating layer-by-layer the structure of the robotic root’s
body [73]. Such systems have opened to the field of ‘plantoids’ and of ‘growing robots’, a category of robots
that are able to self-create their own body and imitate biological growth by incrementally increasing the massof the robot [175] (figure 17).
The field of plant-inspired robotics is new but rapidly expanding, with several examples of technologicalinnovations including osmosis-based actuators for coiling/uncoiling in tendril-like robots [63], actuators
inspired by the carnivorous plants [62, 176], vine-like robots [169, 170], plant-hybrid energy generators[177], climbing plant hooks-inspired attachment systems [178] sensors [179] and swarm communication
strategies [180].
Current and future challenges
Plants use a number of singular strategies to interact with the environment, including complex movements,
sensing, growing and exchange of information with other plants and organisms, that deserve to be further
investigated for innovations in multi-functional materials and for augmenting robot abilities, including theiradaptability, robustness, long-term reliability, predictive modeling, sharing of resources and co-developmentof body and behavior. Such features are of peculiar interest for the design of machines that can act in- andadapt to- unstructured, extreme, and dynamically changing environments.
Focused investigations of plants, which are needed to extract the natural key features useful for the designof the artificial counterpart, are a major challenge for current and future researches in the field ofplant-inspired technologies [173]. There are already studies on the growing mechanisms of shoots and roots,on the dynamic and control of tendrils’ searching and coiling, on the abilities of anchoring of climbing plants[181], on the mechanisms of seeds movement and dispersion [182], or on the mechanisms of plants
communication [183], with relevant results for both scientific and technological perspective.
We need to rethink the new generation of technologies in a more environmentally-friendly andsustainable way, with materials that are multi-functional in terms of actuation, sensing and energy use, andthat are able to evolve or grow depending on the environmental conditions and needed task. This is a major
challenge for reaching a reduced environmental footprint of ICT and no new e-waste. In fact, artificial
systems are still limited on their performance in real environment, in terms of long-term reliability,
autonomy, energy use. In this perspective, plants offer a plethora of inspirational insights to reverse the pointof view of robotic design in a more naturally-integrated way.
To close the circle of biorobotics, plant-inspired robots can be also very interestingly used to better
understand how real plants work. A bioinspired approach, when based on a correct extraction andverification of biological principles, also serves the purpose of providing further tools for studying biology,
which is fundamental to get closer to a full knowledge of the natural systems and to safeguard them.
Advances in science and technology to meet challenges
Nature has carefully tuned bio-materials to enable adaptation in the morphologies and behaviors of all livingorganisms, conferring to the interactions between body and environment a central role in the computationof the system’s actions [174].
Observing and extracting features of such motions and structures require time-lapse recording and tools
for image analysis at micro-level; advances in biomechanical analysis, integrating measurements of38

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Figure 17. On the left, the plantoid robot, first robot inspired by plants with sensorized roots; on the right, a robotic root thatmoves by growing across rocks in unstructured terrains.

mechanical interactions, dynamic modeling and 3D reconstruction taking into account the biological system
within its natural environment; and a successive artificial reproduction with advanced micro-fabrication
techniques [184].
As examples, 3D direct laser lithography has been a revolutionizing technology for replicating
micro-scaled structures present in nature, enabling anchoring of artificial devices over a wide range ofdifferent surfaces [178], or the reproduction of hydrophobic surfaces helping to demonstrate the role ofmicro hairs in Salvinia molesta leaves [185]. Electrospinning is another promising technology for developing
novel biocompatible, biodegradable functional materials [186], used for example, to functionalize artificial
Dionaea-like bistable structures with hygroscopic electrospun nanofibers for activating the state change witha response time of ≈1 s [187].
Extrusion-based fabrication techniques explored already for biomedical applications with large success[188], provide other alternatives for the development of next generation biocompatible robots. 3D
bio-plotters have been used for the realization of shape morphing botanical-like structures [189]; and fused
deposition modeling has been customized and embedded into the first plant-inspired growing robot [73] tomimic the growing mechanism used by plants roots and shoots for movement and exploration.
Taking advantage of these advanced techniques, represents a step forward for pushing the boundaries offabrication and functionalization of components and systems based on multi-functional bio-materials.
Concluding remarks
The perspective of robotics design need to be revised in a more sustainable way, starting from Nature with adeep understanding of natural ecosystems. We need to envision robots as environmentally responsible
machines that can grow, adapt, and are built with biodegradable or recyclable materials [14, 15].
Plants offer a plethora of inspirational insights to reverse the perspective of design of robotic solutions inthis more naturally integrated way. Looking at plants, a new wave of ‘green robots’ can be developed to better
integrate into the natural ecosystem, varying their structural, physiological or behavioral features, as
environmentally-friendly artificial systems.
Cross-disciplinary effort and cross-fertilization between science and engineering, are the keys to reachthis goal, increase the effectiveness of technological applications but also the frequency of scientificdiscoveries, using advanced technologies and bioinspired robots for validating scientific hypothesis and for abetter understanding of species biology and ecology.

Acknowledgments
This work has received funding from the European Union’s Horizon 2020 Research and Innovation
Programme Grant Agreement No. 824074 (‘GrowBot’), the European Union’s Horizon 2020 Research andInnovation Programme Grant Agreement No. 101017940 (‘I-Seed’), and the European Research Council(ERC) under the European Union’s Horizon 2020 Research and Innovation Programme Grant Agreement
No. 101003304 (‘I-Wood’).

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14. Underwater soft robots
Marcello Calisti1,2 and Cecilia Laschi3
1
The BioRobotics Institute, Scuola Superiore Sant’Anna, Italy
2
Lincoln Institute for Agri-food Technology, University of Lincoln, Lincoln, UK
3
Department of Mechanical Engineering, National University of Singapore, Singapore
StatusMarine robotics allowed otherwise impossible underwater operations, dramatically increasing our ability tounderstand the oceans from a scientific perspective, but also to exploit them commercially. Most underwater
robots are pelagic—that is, they move in the water column by mean of thrusters—and, for this reason, theypresent intrinsic limitations when it comes to interacting with the seabed.
Operating in the so-called benthic realm, i.e. very close or in direct contact with the seabed, carries highrisks, especially in coastal areas where the currents and waves disturbances are higher, to accidentally bumpagainst the seabed and damage the robots or the environment. Moreover, the use of propellers introduceshigh levels of acoustic noise in the environment and generates perturbations which raise debris causing
disturbance in the ecosystems and deteriorating the quality of images and sensor readings.
Bioinspiration to benthic marine species in robotics suggests soft bodies, compliant joints and a varietyof locomotion strategies, such as crawling, borrowing, and legged gaits [190], as alternative approaches toincremental research. In this extremely young field, attempts to morph the soft body to increase walking
performance have been demonstrated in lab settings [191]. In underwater real missions, SILVER2 [192, 193],
a medium-size hexapod robot, demonstrated to harness its light underwater weight and elastic elements
integrated in its legs to perform a bioinspired self-stabilizing locomotion to reject the disturbances inducedby irregular terrain, without the need to carefully plan foot placement.
This kind of benthic underwater soft robots can pioneer a new breed of underwater vehicles which will
move over underwater structures, fragile substrates, inside caves or wreckages, and that will collect samples
without disturbing the environment, will perform long-time monitoring, precise and high definition
photography and muscular works when needed. Advances in this field provide tools for biology, geology,
oceanography, offshore industry, and underwater operations in general.

Current and future challenges
Benthic locomotion poses additional challenges with respect to legged locomotion in terrestrial
environments, already successfully implemented in robotics. Underwater legged locomotion is affected bybuoyancy, water drag, added mass, and thus requires locomotion strategies that account for those, as
observed in benthic marine species. Insights and models of benthic locomotion are major challenges on thetheoretical side.
Benthic robotics poses challenges on the materials used for the robot body and components. In order toimplement efficient models for underwater locomotion, soft materials and compliant joints need to be used.
The interaction with the seafloor at the base of benthic locomotion gives contrasting requirements:
compliant body and components are helpful to comply with interaction, collisions, physical constraints; atthe same time, strength is required to apply forces to propel the body forward.
Moreover, materials and structures need to ensure water-insulation to possible electronic components
and to resist pressure. Lastly, robots operating in the benthic environment must ensure not to contaminate it,both in terms of disturbances (noise, sediment perturbation, etc) and in terms of possible dispersion ofpollutants. Ecocompatible and even biodegradable materials could be employed to this purpose.
In terrestrial environments, robots can accurately detect their environment through a number of sensors
and plan their behavior accordingly. Underwater, such detailed mapping is not possible, due to the lack of
accuracy in the sensors, to communication bandwidth limitations given by the water medium, todisturbances in the sensory input, like particle dispersion which limits the use of optical systems. Robot
autonomy stands as a major challenge in underwater robotics, both from the energy and from the control
viewpoint. Most underwater robots are tethered and directly controlled by pilots during operations, and thissame approach could be adopted in benthic robots. However, investigating energy-efficient locomotion,using energy harvesting and exploring new forms of energy transformation are high-potential challenges inthis field. Similarly, providing benthic robots with autonomous behavior represents a value for effective
seabed explorations and resident operations (such as continuous monitoring and maintenance ofunderwater plants).

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Figure 18. The concept of benthic underwater soft robots.

Figure 19. SILVER2 robot.

Advances in science and technology to meet challenges
Biomechanical and behavioral studies of marine species provide insights into locomotion strategies
underwater. The principles extracted from observations and measurements need to be transformed into
mathematical models, usable in engineering, for designing novel benthic robots. At the same time such
benthic robots enable the study of the starting biological models, closing a beneficial loop.
Advances in material science would enable a leap in the field on benthic robots: soft materials that adapt
to environmental niches, smart materials that store energy, materials that biodegrade and SH materials could
answer many of the challenges of effective operation, survival, energy autonomy.
Recent views of intelligence give the physical body a more important role in shaping behavior [194].
Effective sensory-motor behavior is given by the physical interaction of the body with the environment morethan we think. It then depends on mechanical properties and morphological arrangements, while control issimplified to a limited number of control signals or sensory feedbacks. Locomotion is a clear example,
showing how self-stabilizing gaits are given by proper morphologies and compliance, in the extreme extent
with simple, open-loop, controllers. This approach is pivotal underwater, given the limitations in perception.
Investigations on such embodied intelligence and formalization of principles into theories and mathematicalmodels would enable a disruptive progress in benthic robotics.

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Concluding remarks
Soft materials are an important direction of progress for robotics [14]. Soft robotics technologies contributeto a sustainable progress [15] and enable further abilities [195] in underwater robots. Inspired by benthic
marine species, soft robots can negotiate the interaction with the seabed and other underwater structures.
Based on embodied intelligence principles, they gain unprecedent locomotion ability, with self-stabilizing
gaits, efficient computationally and energetically.
Such abilities enable a plethora of applications, underwater. Benthic soft robots can explore the seabed,which is of great interest for studies in biology, ecology, oceanography, and for other scientific purposes. It isof interest for monitoring and management of environmental resources and meteorological services. Benthic
robot abilities also find application in industry, for monitoring and maintenance of underwater plants.
Progresses of the young field of benthic robotics would complement underwater explorations andmonitoring with measurements and operations that have a high social, scientific and industrial impact, andthat are not possible today.

Acknowledgments
This research was partially funded by Arbi Dario S.p.A. under the framework of Blue Resolution project, by
National Geographic Society under the framework of GOLD (Guardian of the Oceans Legged Drone)
project, Grant No. NGS-56544T-19, and by Research England [Lincoln Agri-Robotics] as part of the
Expanding Excellence in England (E3) Programme.

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15. Multifunctionality, adaptability and growth without borders
Wenguang Sun1,2, Gang Wang1,2 and Li Wen1
School of Mechanical Engineering and Automation, Beihang University, Beijing 100191, People’s Republicof China
2
These authors contribute equally to this manuscript.
1

StatusFish have various locomotion capabilities and body morphology that enable them to survive and perform
complex tasks in harsh aquatic environments. Underwater robots’ design can be inspired by the kinematics,
physiology, and anatomy of fish for enhanced maneuverability, stealth, and energy efficiency. In the past
decades, robotics researchers have developed several notable fish-inspired robots. According to fish
swimming modes, fishes can be divided into body and/or caudal fin propulsion (BCF) and media and/or
paired fin propulsion swimmers. In BCF locomotion, body undulation waves are generated, which undulates
towards the caudal fin, thereby producing propulsion. Undulatory biorobotic underwater robots werecommonly used to optimize underwater vehicle performance or investigate scientific questions of fishbiomechanics.
Fins are the most distinctive anatomical features of fishes, and are essential components for maneuvering,stability, sensory feedback. They are composed of several rigid bony spines or rays protruding from the bodywith soft skin covering them and joining them together. Compared with the undulatory flexible body offishes, fins are less understood. In general, fish fins can be divided into median fins and paired fins, which aresupported by a series of segmentally arranged bony or cartilaginous elements, and a wide range of muscles
control the movement of the fin.
Undulatory biorobotic models commonly consisted of multiple rigid segments with static fins, which canswim underwater by rotating each body joint [199–202]. These robots are primarily applied to understandthe effects of morphology and swimming kinematics. Most undulatory biorobotic fish typically operate at
low frequencies (<2 hertz) without exploring high frequency as those of biological fish such as tunas. To
explore the high-frequency fish swimming performance space, Zhu et al designed a tuna robot operating at ahigh frequency up to 15 Hz, exceeding yellowfin tuna (Thunnus albacares) which reach a maximum of 10 Hz
tail beat frequency. Some of the representitive undulatory biorobotic models has shown in figure 20 during
feeding bouts [196].
With the rapid growing of soft robotic technology, robotic fish with soft materials for the body has been
designed in recent years. Driven by an integrated micro hydraulic system, soft robotic fish can exhibit alifelike undulating tail motion that can facilitate a more natural integration in the ocean [197]. Modeled after
redox flow batteries, a soft robotic fish that combines hydraulic force transmission, actuation, and energy
storage creates a circulatory system developed. The energy density of the robot enables operation forextended durations (up to 36 h) [203].
In most previous studies, the fins (tail fin, pectoral fin, dorsal, anal fin) of robotic fish were composed ofsimple sheet-like structures that were static and unable to actively perform shape changes. Morphing finsplay an important role in fish swimming. For example, the robotic fish can realize the forward swimmingwith the undulatory fin even if the fish body remains static [204, 205]. Inspired by bluegill sunfish, Gottlieb
et al developed a pectoral fin that can produce the force and flow to drive the maneuver by achieving
complex three-dimensional motion [206, 207]. One unique example, Hou et al developed an aquatic-aerial
multimodal vehicle with soft morphable fins, which endows a robot to freely shuttle transits between waterand air [208].
From the biomimetic perspective, when characterizing the function of a bioinspired robotic fish, boththe movements of fins (caudal fin, pectoral fin, and dorsal/anal fin) and body deformation should be
included. Based on multimaterial three-dimensional printing, Wen et al fabricated the first undulatory
biomimetic robotic fish with morphing median fins (including a spiny-rayed dorsal fin, soft-rayeddorsal/anal fins, and a caudal fin) whose stiffnesses span three orders of magnitude. An array of fluidic
elastomeric soft actuators was used to mimic the dorsal/anal inclinator and erector/depressor muscles of fish,
which allowed the soft fins to be erected or folded [198, 209]. The morphing fin can significantly increase thelinear acceleration rate by up to 32.5% while decreasing the side force by 24.8%.
The fins of fishes have also evolved other functions rather than swimming and maneuvering. For
example, mudskippers apply their pectoral fins to walk, roll, jump on mud [210]. Remora suckerfish’s firstdorsal fin has been modified to a suction disc to hitchhike on marine animals [211]. Clingfish’s pelvic finscan form and release the suction disc, functioning as a ‘valve’. Therefore, the disc allows clingfish to attach
themselves to the bottom and withstand strong water currents [212]. All these unique features provide
extraordinary inspiration for bio-inspired robots.
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Figure 20. Representative undulatory biorobotic models. (A) Tuna bot that could swim with high frequency. From [196].
Reprinted with permission from AAAS. (B) Acoustically controlled soft robotic fish. From [197]. Reprinted with permission from
AAAS. (C) Instantaneous self-propelled robotic fish with soft morphing median fin. Adapted with permission from [198].
Copyright (2018) Soft Robotics.

In summary, undulatory bio-robotic models were proven to be useful scientific tools for studying fish
fins, and provide further guidance for underwater robotics with fin-inspired apparatus.
Current and future challenges
During the swimming process of the robotic fish, the active movement of the organism imposes disturbanceon the surrounding flow field. At the same time, the flow field imposes a load on the soft material, causing
the soft material to passively deform. With different environmental factors, the properties of soft materials
will even change accordingly. The interaction between the soft material and fluid is very complicated. It isdifficult to calculate and measure the force and the deformation of the soft material. These factors pose greatchallenges to the motion control of soft robotic fish.
Fins can promote swimming and maintain body balance through active and complex three-dimensional
movements, and at the same time can provide sensory feedback of the environments. The realization of thecomplex three-dimensional motion of the bionic fin requires the integration of soft actuators, watertightelectrical control systems, energy storage systems, waterproof sensors, and communication modules.
However, the traditional rigid transmission method has a large volume, a complex structure, and a few
degrees of freedom, and requires a greater driving force. The existing displacement and force sensors have
low sensitivity and insufficient to be used in an underwater environment. These factors restrict the
integration of biomimetic flexible fins with complex three-dimensional motion on the robotic fish body.
Advances in science and technology to meet challenges
PIV technology is a two-dimensional visualization technology of the flow field. Its principle is to use ahigh-energy laser sheet to illuminate the laser particles on a certain layer of the experimental water area, andthen use a high-speed camera to influence and analyse the movement of the laser particles to obtain the Flow
field structure. Three-dimensional PIV can better reveal the complex three-dimensional structure inside theflow field, more deeply reflect the flow mechanism of the flow field, and essentially reflect the nature of theflow field. Three-dimensional PIV has been successfully applied to detect the transverse flow around theswimming fish in the transverse plane, thereby revealing the propulsion and control mechanism of fish
swimming [213].
Computational Fluid Dynamics (CFD) is also another important method for studying fish swimmingand morphing fin. CFD simulation can effectively simulate different swimming modes and flow fieldenvironment, to conduct in-depth research on a certain scientific problem. Based on CFD technology, thepropulsion mechanism of different shapes of caudal fins and the influence of fin morphology changes onswimming during the C-start of fish are well revealed [214–216].
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The fin spines or rays are usually rod-shaped with a tip diameter of a few µm, and require many muscle
groups to actuate. Therefore, the fabrication of the articulated fin is quite challenging. Recent advances in thefield of soft robotics have enabled the development of rapid digital design and manufacturing tools.
Researchers use fast and adaptable manufacturing technologies (including 3D/4D multi-material printing[198], shape deposition manufacturing [217], soft lithography technology [218] and layer-up assembly
methods [219]) to create rigid/soft robotic components at range of scale. These technologies can combine theuse of heterogeneous materials (for example, rubber with different stiffness moduli), embedded electronic
components, and internal channels for driving to make composite materials. Direct digital printing using
soft materials may be another option for making arbitrary soft structures. A variety of fish-inspired roboticorganisms (including undulatory body and morphable fins) can be manufactured using these technologies.
Concluding remarks
New soft materials that can be optical transparent underwater and acoustic transparent in oceanic
environments can be useful for future fish-inspired soft robots. Besides, highly deformable soft active
materials may provide functionalities of morphing to the underwater soft robot, for example, switching fromundulatory to flapping. Moreover, the smart material itself can be used as an actuator of the undulatory
robot fish, which can perform flexible and complex movements for the undulatory body and fins.

Acknowledgments
This work was supported mainly by National Key R&D Program of China grant No. 2018YFB1304600,
2019YFB1309600, 2020YFB1313003. This work was also supported by National Science Foundation of China
grant Nos. 91848105, 91848206, 92048302, T2121003.

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16. Amphibious robots with morphing limbs
Robert Baines, Sree Kalyan Patiballa and Rebecca Kramer-Bottiglio
Department of Mechanical Engineering and Materials Science, Yale University, New Haven, Connecticut
06511, United States of America
StatusBuilding an effective amphibious robot requires integrating structures and programmed behaviours
conducive to both aquatic and terrestrial locomotion within a single robot platform. This design objective ischallenging due to the radically varied environmental profiles amphibious robots must transit. For example,
water exerts buoyant, inertial, and viscous forces; between water and land is the littoral zone, where crashingwaves and fluidized sediment represent high-energy perturbations; on land, gravity presides, and various
substrates of different fracture stresses must be traversed. Due to such environmental differences, animal
morphology is typically optimized for either terrestrial locomotion or aquatic locomotion, but not both.
Through principled engineering, robots have the potential to circumvent the morphologicalcompromises made by amphibious animals. Amphibious robots fall into either of two classes based on theirdesign. The first class comprises those with multiple, physically separate propulsive mechanisms for moving
in the water and on land, like propellers and wheels. The second class includes robots that use one united
propulsive mechanism for movement in both media, such as hybrid paddle-legs or an undulating body. Here
we focus on robots with united propulsive mechanisms, and more specifically, on limbed robots. Advantagesof limbed locomotion include the ability to traverse uneven terrain and engage in a variety of specialized
terrestrial and aquatic gaits.
An emerging paradigm in the design of limbed amphibious robots is to engineer limbs capable ofmorphing between shapes to optimize locomotion for a given environment’s force characteristics [220]. This
paradigm has evolved to favor on-demand changes in limb shape and stiffness using soft, adaptive materials
rather than traditional rigid robotic components. Further research on morphing limbs for amphibious
robots promises to usher in the next generation of mobile robots built from a strategic mix of soft and rigidmaterials. Applications range from bio-monitoring, disaster response, and propulsion study to automateddelivery. Moreover, research on morphing limbs will drive materials innovation to meet the stringent
requirements of in-situ environmental adaptations.
Current and future challenges
There are three significant and interconnected challenges in developing robots capable of effective
amphibious transitions via morphing limbs (figure 21). The first is choosing materials that meet demanding
operational criteria. Limb materials must be robust to degradation in water and failure from repeatedimpacts on land. They must undergo drastic shape changes and preferably, should be able to modulate
stiffness, whether by geometric means or through augmentation of intrinsic material properties. Also, thelimb materials should be disposed to scalable manufacturing techniques. Programming the limb’s shapechange is tied directly to materials selection and manufacture. Some mechanism needs to be conceived tofacilitate the shape change. The designer must consider how an interplay of material non-linearities, limb
geometry, and environmental factors impact morphing performance.
Once the morphing limb is fabricated, it will interface with a robotic platform, which presents a second
challenge: to understand the multiphysics of the robotic system and the environment. The multiphysics
problem includes, but is not limited to, limbed locomotion in the transition zone between water and land.
Little is known about the physics of this zone. Questions include how wave energy and abrasive flows of
sediment could jointly impact the robot’s stability, how substrate yield stress may undermine a specific gait
and shape, and how the limb’s material properties could be impacted by temperature and salinity.
Knowledge of governing physics in the transition zone is a prerequisite to the third challenge of
optimizing limb shape, stiffness, and gait pattern pairings for a locomotion control policy. There are
currently no established control policies for limbed aquatic to terrestrial transition, let alone with theadditional free variables of limb shape and stiffness. When developing a transition policy, the designer might
have to revisit the material selection of the limb to achieve a baseline level of performance.
The nature of these challenges—materials selection, multiphysics modeling, and design optimization—isinterdisciplinary, necessitating collaboration between roboticists, materials scientists, biologists, andphysicists. Fortunately, technological advances are beginning to enable amphibious robots with morphinglimbs.
Advances in science and technology to meet challenges
The first advance in technology to realizing amphibious robots with morphing limbs was a shift from rigid
manually interchanged flippers and legs [221], to hybrid flipper-legs [222]. Noting the inherent performance46

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Figure 21. Abstracted challenges when building and deploying an amphibious robot with morphing limbs. Each challenge isintertwined with the others and must be satisfied in order to achieve successful environmental transitions. The result is aninterdisciplinary, iterative design process.

compromise with hybrid fipper-legs, Liang et al developed morphing limbs from an interlocking compliant
mechanism [223]. Structurally speaking, their limb design still did not enable extreme changes in shape.
Additionally, from a control perspective, all previous limbed amphibious robots have relied on staticallystable, one-degree-of-freedom—per leg terrestrial gaits along with inefficient paddling-based submergedswimming [224].
To tackle the challenge of materials selection for morphing limbs, we note the promising emerging
technologies of hyperelastic fluidic actuators, variable stiffness composites [225], 4D printing, andmetamaterials [226]. With these adaptive material systems, it becomes possible to exploit the intersection ofgeometry and material properties to address drastic programmed shape change, stiffness change, limb
robustness, and scalable manufacture simultaneously. For example, recently, we harnessed the capability offiber-reinforced fluidic actuators coupled to a variable stiffness composite to create a morphing limb
(figure 22(A)). The limb is capable of extreme shape changes between sea turtle and land tortoise—inspired
limb shapes [227]. We attached four morphing limbs to a quadrupedal body with 3DOF shoulder joints(figure 22(B)) for each limb to achieve highly articulated locomotion in water and on land.
Recent work has also begun to address the challenge of understanding the multiphysics of amphibious
robotic transition, starting with the physics of legged locomotion on granular media [228]. Studies like thesemust be expanded to assess how water content and granule size/dispersity influence locomotion. Overall, an
ideal parametric study would controllably vary wave energy, substrate type, incline, and temperature during
a walking-to-swimming transition and vice-versa.
Lastly, control policies must be devised that effectively reject, or conversely, harness environmental
disturbances for productive locomotion. In concert with physics-based models, recent advances in machinelearning can be applied to the transition data to extrapolate viable shape-gait policies across environmental
conditions.

Concluding remarks
Significant obstacles still prevent robots from matching the locomotor efficiency and dexterity of livingorganisms [229]. However, armed with emerging materials technologies and a battery of informed aquatic toterrestrial transition policies, we envision morphing limbs will change the landscape of amphibious robotics,
closing the gap on living organisms. Beyond the specific niche of the aquatic to terrestrial transition, we seemorphing limbs as part of a new and larger trend in the robotics field. A combination of adaptive soft
materials and traditional robotics components synergistically account for each other’s deficiencies, enabling
functionality that purely soft or rigid materials alone cannot accomplish.

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Figure 22. (A) Morphing limbs attached to a quadruped turtle-inspired robot allow it to engage in swimming and walking. The
morphing limb is able to switch between flipper and leg shape using variable stiffness materials and fluidic elastomer actuator.
Reproduced from [227]. © IOP Publishing Ltd. All rights reserved. (B) Schematic showing how a morphing limb interfaces to thekinematic mechanism within the waterproof bellows.

Acknowledgments
This work was supported by the Office of Naval Research under the Young Investigator Program(N00014-17-1-2604). R Baines was supported by the National Science Foundation Graduate Research
Fellowship under Grant DGE-1333468.

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17. Future undersea observatories with soft robotic instruments
Daniela Rus
CSAIL, MIT Schwarzman College of Computing, United States of America
Status
The study of natural intelligence, in its wide variety of forms, is one of the most profound questions inscience today. Understanding the science of intelligence enables the understanding of life itself and supports
the engineering of better systems inspired by nature. Effective studies of natural ecosystems require
observation from afar, so as to not disturb the normal activity of the ecosystem and are especially challenging
in hard to reach underwater environments.
What causes life to thrive in the vast undersea environments? One possible approach to this question is todevelop underwater observatories that can enable long-term studies of behaviors of individual sea life,
interactions among marine life, and influence of the environmental conditions on the marine life. The
observatory generated data which, in turn, can be processed to reveal insights into how life thrives throughintelligent behavior, collaboration, and competition. Undersea observatories can be fixed on the bottom of
the sea, attached to animals, swim alongside marine life, or even placed in the air, above marine ecosystems
of interest. Closeup exploration of wild marine life requires new forms of interaction, using biomimetic
instruments that are capable of agile and stealthy maneuvers, equipped with cameras, and supported byremote human operation. In the recent past, the research community has developed a wide range of robotic
tools for observations, including quadrotor robots (e.g. for tracking Southern Right Whales [230] andpenguins [231]), soft robotic fish (e.g. for exploring underwater coral reef habitats [159, 197, 232, 233]), soft
robotic hands (e.g. for biological sampling in coral reefs [234]) and a variety of networked sensors and softtags [235] that can provide location information for individual animals.
Current and future challenges
Today’s underwater observatories enable very short-term studies, but the existing instruments are either
passive sensors or autonomous robots with time-limited operation and low endurance, due to theiron-board capacity for energy, computation, and data storage required for independent operation. Future
underwater observatories will be fixed on the sea floor, suspended in the water column, or possessautonomous mobility. They will include autonomous instruments for long-term studies and offer
immersible experiences for scientists. They will consist of intelligent robots and sensors capable of life-longoperation, high definition imaging, agile control, live streaming, real-time interaction with humans, and awide range of algorithms for activity recognition, behavior analysis, and communication and interaction
studies. Imagine instruments that are able to capture and convey the experience of being a whale, an octopus,
or a shark. There are a myriad of questions about the lives of undersea animals we are not able to answer
because we cannot place ourselves side by side long-term observations. With soft robotic avatars, scientists
and citizens will be able to virtually attach to an undersea animal or penetrate a group to experience life fromtheir point of view. This in turn will allow us to unravel the mysteries of the undersea life, better understandtheir behaviors and interactions, and even decode their language. With these approaches, in the future wemight even begin to communicate to the whales!
Marine biologists have long experienced the challenges of documenting ocean life, with many species offish proving quite sensitive to the underwater movements of humans. While multiple types of robotic
instruments exist, of particular interest are the soft robots, whose bodies are made out of intrinsically soft
and/or extensible materials (e.g. silicone rubbers) move by undulation and thus can more naturally integrate
in the undersea ecosystems. The bodies of soft robots have a continuously deformable structure withmuscle-like actuation that emulates biological systems and provides them with a relatively large number ofdegrees of freedom as compared to their hard-bodied counterparts. Soft robots have capabilities beyond
what is possible with today’s rigid-bodied robots. Soft bodied robots can move in more natural and quieter
ways. They bend and twist with complex curvatures and adapt their shape to their environments; they arecapable of rapid agile maneuvers; and they can change their stiffness to achieve a task- or
environment-specific impedance.
This vision involves challenges at the intersection of materials science, robotics, computer science,physics, mechanical engineering, and electrical engineering that our interdisciplinary team is poised totackle.
Advances in science and technology to meet challenges
Current research on device-level and algorithmic aspects of soft robots has resulted in a range of novel soft
devices [236–238] including soft robotic fish (figure 23, [197]) and soft robotic starfish (figure 24, [239]).
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Figure 23. SoFi, the soft robotic fish swimming in a coral [236]. Photo credit: Joseph DelPreto.

Figure 24. A soft underwater starfish robot. Photo credit: Josie Hughes. Reproduced from [239]. CC BY 4.0.

Such underwater soft robots are challenging to model and control because of their high degrees of freedom
and their intricate coupling with water. For underwater operation, the complex dynamics of how water
moves and the challenges with making self-contained water tight systems have made soft underwater robots
especially difficult to develop compared to ones for air or land. Additionally, the computational intelligenceand control of these robots has been sparsely addressed. How do we get to the point where soft robots deliver
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B Mazzolai et alon their full potential to enable undersea observatories? This requires breakthroughs in: (a) rapid design
tools and fabrication recipes for low-cost soft robots; (b) new algorithmic approaches to the modeling,
optimizing, and control of soft robots that include—and exploit—their unique material properties; and (c)capable new systems that demonstrate the benefits of this technology and encourage broad early adopters.
Such advances will lead to soft robots that have the ability to compute, sense, and move, leading to aconvergence between materials and machines, with materials becoming more intelligent due to embedded
electro-mechanical components, and machines becoming softer due to the alternative materials used tocreate them. This convergence requires tools for functional specification and automated co-design of the softbody (including all the components necessary for actuation, sensing, and computation) and the soft brain(including all software aspects of controlling the device and reasoning about the world and the goal task).
Progress in new materials with programmable stiffness properties, proprioceptive sensing, contact modeling,
and recipes for rapid fabrication will enable the creation of increasingly more capable soft machines.
Additionally, soft robots to date have been impoverished in terms of sensing. Developing dense sensor skinfor soft robots will allow these systems to explore the world of high definition touch which in turn will impact
their performance. Dense sensor skins will provide the robots with proprioceptive capabilities (to recognize
what they are touching) and with exteroceptive capabilities (to respond compliantly to their environment).
Concluding remarks
Creating the future of Undersea Observatories involves challenges at the intersection of materials science,robotics, computer science, physics, mechanical engineering, and electrical engineering that ourinterdisciplinary team is poised to tackle. This will result in the science-base for soft, strong, and safe
configurable robots that can adapt to a variety of tasks and environments, as well as a suite of devices toenable the future undersea observatories.
Bio-inspired robots like the starfish robot and SoFi can get closer to marine life without disturbing it. In
the future, by rapidly designing and building bio-inspired robotic instruments, it will be possible to createcustom observatories that can be deployed in the wilderness to observe life.

Acknowledgments
We gratefully acknowledge the following support: NSF Grant No. EFRI-1830901, IARPA Grant No.
2019-19020100001, and DARPA Grant No. FA8750-20-C-0075.

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18. Nanoscale soft robots
Peer Fischer1,2 and Friedrich C Simmel3
1
Max Planck Institute for Intelligent Systems, Heisenbergstr. 3, 70569 Stuttgart, Germany
2
Institute of Physical Chemistry, University of Stuttgart, Pfaffenwaldring 55, Stuttgart 70569, Germany
3
Physics Department E14, Technical University Munich, 85748 Garching, Germany
StatusA nanorobot should embody the robotic functions of action, sensing, information processing and possibly
communication at the nanoscale, i.e. at a scale that is smaller than a bacterial cell. Assuming that nanorobots
will operate in liquids, and since motion is highly damped at these small scales, they are thus inherently ‘soft’,
regardless of the actual material they are made of. This is in contrast to large scale robotic systems, where it isa challenge to find soft motors and actuators. Nevertheless, molecular motors, polymers and DNA play animportant role in realizing increased function, control and autonomy on these tiny length scales.
It has proven difficult to realize autonomous nanorobotic systems. Many studies have thus far either
focused on implementing only one or at most two functions and/or have relied on external macroscopic
support systems that operate in conjunction with the nanoscopic agents. However, recent advances inchemistry, soft matter physics, biophysics, and nanotechnology have shown that some robotic functions canbe entirely realized in molecular or nanoscale systems, at least in principle (see figure 25). For instance,supramolecular chemistry as well as DNA nanotechnology have successfully demonstrated synthetic
molecular switches, machines and motors, potentially acting as sensors and actuators of nanoscale robots.
DNA is particularly attractive, as it is intrinsically an information-encoding molecule and lends itself for
DNA-based molecular computing. Further, DNA nanotechnology—notably the so-called ‘DNA origami’technique—has enabled the sequence-programmable self-assembly of almost arbitrarily shaped molecular
objects [240]. Furthermore, various chemical and physical mechanisms have been employed to switch
conformations, and to realize linear walkers and rotatory molecular motors. Thus, in principle, all the major
functional components of a robotic system can be realized with DNA alone [241–243].
A parallel area of research concerns the fabrication of inorganic or polymeric nanostructures and theircontrol by external fields, such as magnetic or light fields that induce changes in body shape analogous tothose found in biological microswimmers [244]. A further promising recent development is based on the
integration of non-equilibrium systems. Similar to the machinery of life, a chemical fuel drives this form of‘active matter’. One exciting prospect besides the locomotion via self-phoresis is that active systems are ameans to realizing ‘autonomous’ behaviors and that they show collective effects [245].
Current and future challenges
While the prototypes demonstrated thus far are promising, many challenges remain. First, the information
processing capabilities of individual molecular structures are quite limited—essentially, they are based on
switching between two (or a few) states, which means that their computational power compares with(simple) finite state machines. Second, many of the molecular processes involved are relatively slow andtherefore cannot respond quickly enough to changes in the environment. Third, nanorobots are, of course,
small, which makes it difficult to integrate them into larger systems, or to let them locomote across larger
length scales, especially as they need to fight Brownian fluctuations. This calls for new modes of operationthat differ from those of macroscopic robots, as well as efficient means to integrate large numbers ofmolecular units to form a collective system.
While the nanorobotic systems based on inorganic or polymeric particles may be more readilytransported over macroscopic distances, it remains a challenge to implement the versatility and information
processing capabilities of molecular machines. The chemically fueled self-phoretic swimmers work well inhigh energy toxic fuels, but struggle to achieve efficient propulsion in physiological environments.
Light-actuated polymeric systems show little autonomy and often rely on temperature-induced
shape-changes, where an extension to the mechanochemical mechanisms of molecular motors would
significantly widen the design space. Medical applications will also require that the materials and structures
are fully biocompatible, although some promising biocompatible systems have been identified inmagnetically actuated systems [247]. Another challenge that is common to all systems, is the need to increase
the force that can be locally achieved so that they may perform useful functions, such as entering a dense
tissue. Therefore, much remains to be shown to advance the field.
Advances in science and technology to meet challenges
Multiscale and hybrid robotics
It is hard to beat electronic computers using the limited capabilities of molecules alone—on the other hand,molecular robots are at the right scale to interact with other molecular (and biological) systems. Nanorobots
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Figure 25. Nanorobotic systems realized with supramolecular building blocks (a), (b) or with chemically-active building blocks(c). External field control (d) is a hallmark of many systems thus far, including some DNA-based systems (a). A few nanorobotic
systems show some degree of autonomous operation. A separate field of study, which we do not consider here, concerns
nanorobotic manipulation systems [246], which are primarily based on large scale equipment for positioning with nanometer
resolution. Reproduced from CC BY 4.0.

in this case act as bodies with sensors and actuators—the control is outsourced [248]. Advances in imaging
are required to permit this approach to work in complex and opaque environments. Most
magnetically-controlled systems require bulky instrumentation that is difficult to scale up for realhuman-scale medical applications and here it becomes necessary to develop new technologies. While this isan engineering challenge, the scientific challenge also remains, that in principle it should be possible torealize synthetic analogs to the machinery of life, and thus autonomous molecular-based nanorobots should
be possible without recourse to outside support systems.
Active matter in soft robotics
Much of the self-assembly and self-organization in biological cellular systems is based on sophisticatednon-equilibrium processes. An interesting research direction is therefore to combine active matter with
precisely tailored molecular building blocks (made from, e.g. DNA origami). Another exciting possibility is to
encode functions found in biological systems, such as artificial chemotaxis. One may thus envision a systemwith active motion powered by a chemical reaction, in which the nanorobot adapts to the environment,
controls the direction of motion and ultimately facilitates the delivery of a molecular cargo to a target.
Swarms and other collective phenomena
In order to overcome the limitations of single nanorobots with limited capabilities, a conceivable strategy is
to couple the robots via some physical or chemical interaction and let them move, compute, operatecollectively. Similar to the molecular motors that collectively cause macroscopic muscle contractions, here
Avogadro’s number of molecular machines and nanorobots could work together and cause effects on the
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macroscopic scale. First steps in this direction have been taken by emulating population-based
decision-making processes such as the ‘quorum sensing’ phenomenon known from bacteria [249]. Physicalcoupling can lead to apparent ‘swarming’ behavior of active particles, which may be useful in this context.
Concluding remarks
The road ahead
The capabilities of nanorobotic systems will be dramatically extended when the fields of mechanochemistry,
molecular robotics, DNA nanotechnology and active nanosystems join forces, the aim being to realize faster
actuators, utilize cooperative effects and implement information processing. Given the limited computing
power, nanorobotics needs to develop its own form of embodied computation. Essentially, input-output
relationships between sensor and actuator functions need to be directly encoded in the material. A
fascinating and entirely open question is how one may achieve learning with soft physicochemical systems.
The nanorobots that are powered from the outside face the perpetual challenge of how energy is mostefficiently transferred to the nanoscale, and how stronger forces can be exerted. Progress in this field will also
spur other technological developments. Solving a real-world problem that finds application outside a
research lab will be a major milestone. However, already answering the fundamental questions that arise innanorobotics is set to impact a number of fields.

Data availability statement
No new data were created or analysed in this study.

ORCID iDs
Federico Carpi  https://orcid.org/0000-0001-8496-5085
Koichi Suzumori  https://orcid.org/0000-0002-5735-4956
Matteo Cianchetti  https://orcid.org/0000-0002-9016-8039
Thomas Speck  https://orcid.org/0000-0002-2245-2636
Stoyan K Smoukov  https://orcid.org/0000-0003-1738-818X
Ingo Burgert  https://orcid.org/0000-0003-0028-072X
Felix Vanneste  https://orcid.org/0000-0002-8133-391X
Olivier Goury  https://orcid.org/0000-0002-8616-350X
Christian Duriez  https://orcid.org/0000-0001-6030-7117
Thrishantha Nanayakkara  https://orcid.org/0000-0002-1882-1232
Joost Brancart  https://orcid.org/0000-0002-1735-1515
Steven I Rich  https://orcid.org/0000-0003-3859-4767
Ruiyuan Liu  https://orcid.org/0000-0002-1678-3500
Kenjiro Fukuda  https://orcid.org/0000-0001-8015-5819
Takao Someya  https://orcid.org/0000-0003-3051-1138
Marcello Calisti  https://orcid.org/0000-0002-2590-188X
Cecilia Laschi  https://orcid.org/0000-0001-5248-1043
Wenguang Sun  https://orcid.org/0000-0001-9581-7416
Gang Wang  https://orcid.org/0000-0003-2134-7161
Li Wen  https://orcid.org/0000-0002-1498-3103
Robert Baines  https://orcid.org/0000-0002-9023-1536
Sree Kalyan Patiballa  https://orcid.org/0000-0002-0107-4912
Daniela Rus  https://orcid.org/0000-0001-5473-3566
Peer Fischer  https://orcid.org/0000-0002-8600-5958
Friedrich C Simmel  https://orcid.org/0000-0003-3829-3446
Andreas Lendlein  https://orcid.org/0000-0003-4126-4670

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