Soft robotics draws heavily from the way in which living organisms move and adapt to their surroundings. In contrast to robots built from rigid materials, soft robots allow for increased flexibility and adaptability for accomplishing tasks, as well as improved safety when working around humans. These characteristics allow for its potential use in the fields of medicine and manufacturing.
Types and designs
The goal of soft robotics is the design and construction of robots with physically flexible-bodies and electronics. Sometimes softness is limited to part of the machine. For example, rigid-bodied robotic arms can employ soft end effectors to gently grab and manipulate delicate or irregularly shaped objects. Most rigid-bodied mobile robots also strategically employ soft components, such as foot pads to absorb shock or springy joints to store/release elastic energy. However, the field of soft robotics generally leans toward machines that are predominately or entirely soft. Robots with entirely soft bodies have tremendous potential. For one their flexibility allows them to squeeze into places rigid bodies cannot, which could prove useful in disaster relief scenarios. Soft robots are also safer for human interaction and for internal deployment inside a human body.
Nature is often a source of inspiration for soft robot design given that animals themselves are mostly composed of soft components and they appear to exploit their softness for efficient movement in complex environments almost everywhere on Earth . Thus, soft robots are often designed to look like familiar creatures, especially entirely soft organisms like octopuses. However, it is extremely difficult to manually design and control soft robots given their low mechanical impedance. The very thing that makes soft robots beneficial—their flexibility and compliance—makes them difficult to control. The mathematics developed over the past centuries for designing rigid bodies generally fail to extend to soft robots. Thus, soft robots are commonly designed in part with the help of automated design tools, such as evolutionary algorithms, which enable a soft robot's shape, material properties, and controller to all be simultaneously and automatically designed and optimized together for a given task .
Plant cells can inherently produce hydrostatic pressure due to a solute concentration gradient between the cytoplasm and external surroundings (osmotic potential). Further, plants can adjust this concentration through the movement of ions across the cell membrane. This then changes the shape and volume of the plant as it responds to this change in hydrostatic pressure. This pressure derived shape evolution is desirable for soft robotics and can be emulated to create pressure adaptive materials through the use of fluid flow. The following equation models the cell volume change rate:
- is the rate of volume change.
- is the cell membrane.
- is the hydraulic conductivity of the material.
- is the change in hydrostatic pressure.
- is the change in osmotic potential.
This principle has been leveraged in the creation of pressure systems for soft robotics. These systems are composed of soft resins and contain multiple fluid sacs with semi-permeable membranes. The semi-permeability allows for fluid transport that then leads to pressure generation. This combination of fluid transport and pressure generation then leads to shape and volume change.
Another biologically inherent shape changing mechanism is that of hygroscopic shape change. In this mechanism, plant cells react to changes in humidity. When the surrounding atmosphere has a high humidity, the plant cells swell, but when the surrounding atmosphere has a low humidity, the plant cells shrink. This volume change has been observed in pollen grains and pine cone scales.
Conventional manufacturing techniques, such as subtractive techniques like drilling and milling, are unhelpful when it comes to constructing soft robots as these robots have complex shapes with deformable bodies. Therefore, more advanced manufacturing techniques have been developed. Those include Shape Deposition Manufacturing (SDM), the Smart Composite Microstructure (SCM) process, and 3D multimaterial printing.
SDM is a type of rapid prototyping whereby deposition and machining occur cyclically. Essentially, one deposits a material, machines it, embeds a desired structure, deposits a support for said structure, and then further machines the product to a final shape that includes the deposited material and the embedded part. Embedded hardware includes circuits, sensors, and actuators, and scientists have successfully embedded controls inside of polymeric materials to create soft robots, such as the Stickybot and the iSprawl.
SCM is a process whereby one combines rigid bodies of carbon fiber reinforced polymer (CFRP) with flexible polymer ligaments. The flexible polymer act as joints for the skeleton. With this process, an integrated structure of the CFRP and polymer ligaments is created through the use of laser machining followed by lamination. This SCM process is utilized in the production of mesoscale robots as the polymer connectors serve as low friction alternatives to pin joints.
3D printing can now be used to print a wide range of silicone inks using Robocasting also known as direct ink writing (DIW). This manufacturing route allows for a seamless production of fluidic elastomer actuators with locally defined mechanical properties. It further enables a digital fabrication of pneumatic silicone actuators exhibiting programmable bioinspired architectures and motions. A wide range of fully functional softrobots have been printed using this method including bending, twisting, grabbing and contracting motion. This technique avoids some of the drawbacks of conventional manufacturing routes such as delamination between glued parts. Another additive manufacturing method that produces shape morphing materials whose shape is photosensitive, thermally activated, or water responsive. Essentially, these polymers can automatically change shape upon interaction with water, light, or heat. One such example of a shape morphing material was created through the use of light reactive ink-jet printing onto a polystyrene target. Additionally, shape memory polymers have been rapid prototyped that comprise two different components: a skeleton and a hinge material. Upon printing, the material is heated to a temperature higher than the glass transition temperature of the hinge material. This allows for deformation of the hinge material, while not affecting the skeleton material. Further, this polymer can be continually reformed through heating.
Control methods and materials
All soft robots require an actuation system to generate reaction forces, to allow for movement and interaction with its environment. Due to the compliant nature of these robots, soft actuation systems must be able to move without the use of rigid materials that would act as the bones in organisms, or the metal frame that is common in rigid robots. Nevertheless, several control solutions to soft actuation problem exist and have found its use, each possessing advantages and disadvantages. Some examples of control methods and the appropriate materials are listed below.
One example is utilization of electrostatic force that can be applied in:
- Dielectric Elastomer Actuators (DEAs) that use high-voltage electric field in order to change its shape (example of working DEA). These actuators can produce high forces, have high specific power (W kg−1), produce large strains (>1000%), possess high energy density (>3 MJ m−3), exhibit self-sensing, and achieve fast actuation rates (10 ms - 1 s). However, the need for high-voltages quickly becomes the limiting factor in the potential practical applications. Additionally, these systems often exhibit leakage currents, tend to have electrical breakdowns (dielectric failure follows Weibull statistics therefore the probability increases with increased electrode area ), and require pre-strain for the greatest deformation. Some of the new research shows that there are ways of overcoming some of these disadvantages, as shown e.g. in Peano-HASEL actuators, which incorporate liquid dielectrics and thin shell components. These approach lowers the applied voltage needed, as well as allows for self-healing during electrical breakdown.
- Shape memory polymers (SMPs) are smart and reconfigurable materials that serve as an excellent example of thermal actuation that can be used for actuation. These materials will "remember" their original shape and will revert to it upon temperature increase. For example, crosslinked polymers can be strained at temperatures above their glass-transition (Tg) or melting-transition (Tm) and then cooled down. When the temperature is increased again, the strain will be released and materials shape will be changed back to the original. This of course suggests that there is only one irreversible movement, but there have been materials demonstrated to have up to 5 temporary shapes. One of the simplest and best known examples of shape memory polymers is a toy called Shrinky Dinks that is made of pre-stretched polystyrene (PS) sheet which can be used to cut out shapes that will shrink significantly when heated. Actuators produced using these materials can achieve strains up to 1000% and have demonstrated a broad range of energy density between <50 kJ m−3 and up to 2 MJ m−3. Definite downsides of SMPs include their slow response (>10 s) and typically low force generated. Examples of SMPs include polyurethane (PU), polyethylene teraphtalate (PET), polyethyleneoxide (PEO) and others.
- Shape memory alloys are behind another control system for soft robotic actuation.  Although made of metal, a traditionally rigid material, the springs are made from very thin wires and are just as compliant as other soft materials. These springs have a very high force-to-mass ratio, but stretch through the application of heat, which is inefficient energy-wise.
- Pneumatic artificial muscles, another control method used in soft robots, relies on changing the pressure inside a flexible tube. This way it will act as a muscle, contracting and extending, thus applying force to what it's attached to. Through the use of valves, the robot may maintain a given shape using these muscles with no additional energy input. However, this method generally requires an external source of compressed air to function. Proportional Integral Derivative (PID) controller is the most commonly used algorithm for pneumatic muscles. The dynamic response of pneumatic muscles can be modulated by tuning the parameters of the PID controller.
Uses and applications
Soft robots can be implemented in the medical profession, specifically for invasive surgery. Soft robots can be made to assist surgeries due to their shape changing properties. Shape change is important as a soft robot could navigate around different structures in the human body by adjusting its form. This could be accomplished through the use of fluidic actuation.
Soft robots may also be used for the creation of flexible exosuits, for rehabilitation of patients, assisting the elderly, or simply enhancing the user's strength. A team from Harvard created an exosuit using these materials in order to give the advantages of the additional strength provided by an exosuit, without the disadvantages that come with how rigid materials restrict a person's natural movement. The exosuits are metal frameworks fitted with motorized muscles to multiply the wearer’s strength. Also called exoskeletons, the robotic suits’ metal framework somewhat mirrors the wearer’s internal skeletal structure.
The suit makes lifted objects feel much lighter, and sometimes even weightless, reducing injuries and improving compliance.
Traditionally, manufacturing robots have been isolated from human workers due to safety concerns, as a rigid robot colliding with a human could easily lead to injury due to the fast-paced motion of the robot. However, soft robots could work alongside humans safely, as in a collision the compliant nature of the robot would prevent or minimize any potential injury.
An application of bio-mimicry via soft robotics is in ocean or space exploration. In the search for extraterrestrial life, scientists need to know more about extraterrestrial bodies of water, as water is the source of life on Earth. Soft robots could be used to mimic sea creatures that can efficiently maneuver through water. Such a project was attempted by a team at Cornell in 2015 under a grant through NASA’s Innovative Advanced Concepts (NIAC). The team set out to design a soft robot that would mimic a lamprey or cuttlefish in the way it moved underwater, in order to efficiently explore the ocean below the ice layer of Jupiter's moon, Europa. But exploring a body of water, especially one on another planet, comes with a unique set of mechanical and materials challenges.
Mechanical Considerations in Design
Fatigue failure from flexing
Soft robots, particularly those designed to imitate life, often must experience cyclic loading in order to move or do the tasks for which they were designed. For example, in the case of the lamprey- or cuttlefish-like robot described above, motion would require electrolyzing water and igniting gas, causing a rapid expansion to propel the robot forward. This repetitive and explosive expansion and contraction would create an environment of intense cyclic loading on the chosen polymeric material. A robot underwater and/or on Europa would be nearly impossible to patch up or replace, so care would need to be taken to choose a material and design that minimizes initiation and propagation of fatigue-cracks. In particular, one should choose a material with a fatigue limit, or a stress-amplitude frequency above which the polymer’s fatigue response is no longer dependent on the frequency.
Brittle failure when cold
Secondly, because soft robots are made of highly compliant materials, one must consider temperature effects. The yield stress of a material tends to decrease with temperature, and in polymeric materials this effect is even more extreme. At room temperature and higher temperatures, the long chains in many polymers can stretch and slide past each other, preventing the local concentration of stress in one area and making the material ductile. But most polymers undergo a ductile-to-brittle transition temperature below which there is not enough thermal energy for the long chains to respond in that ductile manner, and fracture is much more likely. The tendency of polymeric materials to turn brittle at cooler temperatures is in fact thought to be responsible for the Space Shuttle Challenger disaster, and must be taken very seriously, especially for soft robots that will be implemented in medicine. A ductile-to-brittle transition temperature need not be what one might consider "cold," and is in fact characteristic of the material itself, depending on its crystallinity, toughness, side-group size (in the case of polymers), and other factors.
- Soft Robotics (SoRo)
- Soft Robotics section of Frontiers in Robotics and AI
- 2018 Robosoft, first IEEE International Conference on Soft Robotics, April 24–28, 2018, Livorno, Italy
- 2017 IROS 2017 Workshop on Soft Morphological Design for Haptic Sensation, Interaction and Display, 24 September 2017, Vancouver, BC, Canada
- 2016 First Soft Robotics Challenge, April 29–30, Livorno, Italy
- 2016 Soft Robotics week, April 25–30, Livorno, Italy
- 2015 "Soft Robotics: Actuation, Integration, and Applications – Blending research perspectives for a leap forward in soft robotics technology" at ICRA2015, Seattle WA
- 2014 Workshop on Advances on Soft Robotics, 2014 Robotics Science an Systems (RSS) Conference, Berkeley, CA, July 13, 2014
- 2013 International Workshop on Soft Robotics and Morphological Computation, Monte Verità, July 14–19, 2013
- 2012 Summer School on Soft Robotics, Zurich, June 18–22, 2012
In popular culture
The 2014 Disney film Big Hero 6 features a soft robot, Baymax, originally designed for use in the healthcare industry. In the film, Baymax is portrayed as a large yet unintimidating robot with an inflated vinyl exterior surrounding a mechanical skeleton. The basis of Baymax concept comes from real life research on applications of soft robotics in the healthcare field, such as roboticist Chris Atkeson's work at Carnegie Mellon's Robotics Institute.
- Articulated soft robotics
- Octobot (robot)
- Bio-inspired robotics
- Home robot
- Robotic materials
- Soft Growing Robotics
- Soft Robot - A Review (Elveflow )
- Dielectric elastomer actuators (softroboticstoolkit.com)
- HEASEL actuators: soft muscles (nextbigfuture.com).
- Trivedi, D., Rahn, C. D., Kier, W. M., & Walker, I. D. (2008). Soft robotics: Biological inspiration, state of the art, and future research. Applied Bionics and Biomechanics, 5(3), 99-117.
- Rus, Daniela; Tolley, Michael T. (27 May 2015). "Design, fabrication and control of soft robots" (PDF). Nature. 521 (7553): 467–475. Bibcode:2015Natur.521..467R. doi:10.1038/nature14543. hdl:1721.1/100772. PMID 26017446.
- Kim, Sangbae; Laschi, Cecilia; Trimmer, Barry (2013). "Soft robotics: a bioinspired evolution in robotics". Trends in Biotechnology. 31 (5): 287–94. doi:10.1016/j.tibtech.2013.03.002. PMID 23582470.
- Bongard, Josh (2013). "Evolutionary Robotics". Communications of the ACM. 56 (8): 74–83. doi:10.1145/2492007.2493883.
- Li, Suyi; Wang, K. W. (1 January 2017). "Plant-inspired adaptive structures and materials for morphing and actuation: a review". Bioinspiration & Biomimetics. 12 (1): 011001. Bibcode:2017BiBi...12a1001L. doi:10.1088/1748-3190/12/1/011001. ISSN 1748-3190. PMID 27995902.
- Dumais, Jacques; Forterre, Yoël (21 January 2012). ""Vegetable Dynamicks": The Role of Water in Plant Movements". Annual Review of Fluid Mechanics. 44 (1): 453–478. Bibcode:2012AnRFM..44..453D. doi:10.1146/annurev-fluid-120710-101200.
- Katifori, Eleni; Alben, Silas; Cerda, Enrique; Nelson, David R.; Dumais, Jacques (27 April 2010). "Foldable structures and the natural design of pollen grains" (PDF). Proceedings of the National Academy of Sciences. 107 (17): 7635–7639. Bibcode:2010PNAS..107.7635K. doi:10.1073/pnas.0911223107. PMC 2867878. PMID 20404200.
- Dawson, Colin; Vincent, Julian F. V.; Rocca, Anne-Marie (18 December 1997). "How pine cones open". Nature. 390 (6661): 668. Bibcode:1997Natur.390..668D. doi:10.1038/37745.
- Cho, Kyu-Jin; Koh, Je-Sung; Kim, Sangwoo; Chu, Won-Shik; Hong, Yongtaek; Ahn, Sung-Hoon (11 October 2009). "Review of manufacturing processes for soft biomimetic robots". International Journal of Precision Engineering and Manufacturing. 10 (3): 171–181. doi:10.1007/s12541-009-0064-6.
- Kim, S.; Spenko, M.; Trujillo, S.; Heyneman, B.; Mattoli, V.; Cutkosky, M. R. (1 April 2007). Whole body adhesion: hierarchical, directional and distributed control of adhesive forces for a climbing robot. Proceedings 2007 IEEE International Conference on Robotics and Automation. pp. 1268–1273. CiteSeerX 10.1.1.417.3488. doi:10.1109/ROBOT.2007.363159. ISBN 978-1-4244-0602-9.
- Cham, Jorge G.; Bailey, Sean A.; Clark, Jonathan E.; Full, Robert J.; Cutkosky, Mark R. (1 October 2002). "Fast and Robust: Hexapedal Robots via Shape Deposition Manufacturing". The International Journal of Robotics Research. 21 (10–11): 869–882. doi:10.1177/0278364902021010837. ISSN 0278-3649.
- Schaffner, Manuel; Faber, Jakbo A.; Pianegonda, Lucas R.; Rühs, Patrick A.; Coulter, Fergal; Studart, André R. (2018-02-28). "3D printing of robotic soft actuators with programmable bioinspired architectures". Nature Communications. 9 (1): 878. Bibcode:2018NatCo...9..878S. doi:10.1038/s41467-018-03216-w. PMC 5830454. PMID 29491371.
- Truby, Ryan L.; Lewis, Jennifer A. (14 December 2016). "Printing soft matter in three dimensions". Nature. 540 (7633): 371–378. Bibcode:2016Natur.540..371T. doi:10.1038/nature21003. PMID 27974748.
- Bauer, Siegfried; Suo, Zhigang; Baumgartner, Richard; Li, Tiefeng; Keplinger, Christoph (2011-12-08). "Harnessing snap-through instability in soft dielectrics to achieve giant voltage-triggered deformation". Soft Matter. 8 (2): 285–288. doi:10.1039/C1SM06736B. ISSN 1744-6848.
- Koh, Soo Jin Adrian; Zhao, Xuanhe; Suo, Zhigang (June 2009). "Maximal energy that can be converted by a dielectric elastomer generator". Applied Physics Letters. 94 (26): 26. Bibcode:2009ApPhL..94z2902K. doi:10.1063/1.3167773.
- Diaham, S.; Zelmat, S.; Locatelli, M.-; Dinculescu, S.; Decup, M.; Lebey, T. (February 2010). "Dielectric breakdown of polyimide films: Area, thickness and temperature dependence". IEEE Transactions on Dielectrics and Electrical Insulation. 17 (1): 18–27. doi:10.1109/TDEI.2010.5411997. ISSN 1070-9878.
- Hines, Lindsey; Petersen, Kirstin; Lum, Guo Zhan; Sitti, Metin (2017). "Soft Actuators for Small-Scale Robotics". Advanced Materials. 29 (13): 1603483. doi:10.1002/adma.201603483. ISSN 1521-4095. PMID 28032926.
- Keplinger, C.; Radakovitz, M.; King, M.; Benjamin, C.; Emmett, M. B.; Morrissey, T. G.; Mitchell, S. K.; Acome, E. (2018-01-05). "Hydraulically amplified self-healing electrostatic actuators with muscle-like performance". Science. 359 (6371): 61–65. Bibcode:2018Sci...359...61A. doi:10.1126/science.aao6139. ISSN 1095-9203. PMID 29302008.
- Keplinger, Christoph; Mitchell, Shane K.; Smith, Garrett M.; Venkata, Vidyacharan Gopaluni; Kellaris, Nicholas (2018-01-05). "Peano-HASEL actuators: Muscle-mimetic, electrohydraulic transducers that linearly contract on activation". Science Robotics. 3 (14). eaar3276. doi:10.1126/scirobotics.aar3276. ISSN 2470-9476.
- Mather, P. T.; Qin, H.; Liu, C. (2007-04-10). "Review of progress in shape-memory polymers". Journal of Materials Chemistry. 17 (16): 1543–1558. doi:10.1039/B615954K. ISSN 1364-5501.
- Peng, Yuxing; Ding, Xiaobin; Zheng, Zhaohui; Pan, Yi; Xia, Shuang; Liu, Tuo; Li, Jing (2011-08-09). "A versatile approach to achieve quintuple-shape memory effect by semi-interpenetrating polymer networks containing broadened glass transition and crystalline segments". Journal of Materials Chemistry. 21 (33): 12213–12217. doi:10.1039/C1JM12496J. ISSN 1364-5501.
- Langer, Robert; Lendlein, Andreas (2002-05-31). "Biodegradable, Elastic Shape-Memory Polymers for Potential Biomedical Applications". Science. 296 (5573): 1673–1676. Bibcode:2002Sci...296.1673L. doi:10.1126/science.1066102. ISSN 1095-9203. PMID 11976407.
- Anthamatten, Mitchell; Roddecha, Supacharee; Li, Jiahui (2013-05-28). "Energy Storage Capacity of Shape-Memory Polymers". Macromolecules. 46 (10): 4230–4234. Bibcode:2013MaMol..46.4230A. doi:10.1021/ma400742g. ISSN 0024-9297.
- Medina, Oded; Shapiro, Amir; Shvalb, Nir (2015). "Kinematics for an Actuated Flexible n-Manifold". Journal of Mechanisms and Robotics. 8 (2): 021009. doi:10.1115/1.4031301. ISSN 1942-4302.
- Kim, Sangbae; Laschi, Cecilia; Trimmer, Barry (May 2013). "Soft robotics: a bioinspired evolution in robotics". Trends in Biotechnology. 31 (5): 287–294. doi:10.1016/j.tibtech.2013.03.002. PMID 23582470.
- Guan, Nan; Wang, Qixin; Li, Shuai; Shao, Zili; Khan, Ameer Hamza; Khan, Ameer Hamza; Shao, Zili; Li, Shuai; Wang, Qixin; Guan, Nan (March 2020). "Which is the Best PID Variant for Pneumatic Soft Robots? An Experimental Study". IEEE/CAA Journal of Automatica Sinica. 7 (2): 1–10.
- Cianchetti, Matteo; Ranzani, Tommaso; Gerboni, Giada; Nanayakkara, Thrishantha; Althoefer, Kaspar; Dasgupta, Prokar; Menciassi, Arianna (1 June 2014). "Soft Robotics Technologies to Address Shortcomings in Today's Minimally Invasive Surgery: The STIFF-FLOP Approach". Soft Robotics. 1 (2): 122–131. doi:10.1089/soro.2014.0001. ISSN 2169-5172.
- Walsh, Conor; Wood, Robert (5 August 2016). "Soft Exosuits". Wyss Institute. Retrieved 27 April 2017.
- "Soft robot to swim through Europa's oceans". Cornell Chronicle. Retrieved 2019-05-23.
- Courtney, Thomas H. (2000). Mechanical behavior of materials (2nd ed.). Boston: McGraw Hill. ISBN 0070285942. OCLC 41932585.
- "MIT School of Engineering | » Why do plastics get brittle when they get cold?". Mit Engineering. Retrieved 2019-05-23.
- "Brittle-Ductile Transition". polymerdatabase.com. Retrieved 2019-05-23.
- Ulanoff, Lance (7 November 2014). "'Big Hero 6' star Baymax was inspired by a real robot". Mashable. Retrieved 20 January 2019.
- Trimboli, Brian (Nov 9, 2014). "CMU's soft robotics inspire Disney's movie Big Hero 6 – The Tartan". The Tartan. Carnegie Mellon University. Retrieved 2016-08-15.