Traditionally robots are imagined as tough, rigid machines that are highly resistant to damage. However, these machines are still subject to wear and tear from normal use, or can be damaged, requiring expensive repairs that also impact productivity.

What if robots could heal from injuries much like how people do? Soft robotics is a growing discipline where engineers create robots made of flexible, pliable materials. Gone are the days where robots are almost strictly made of plastics, alloys and electronics.

This expanding subfield has major applications in aerospace, healthcare and manufacturing. Soft robots can work more closely with humans, when combined with other technologies. Not only are they safer for their human coworkers, but they can potentially be fixed more quickly as well, from materials that are lower cost and have higher workability.

One such example emerged from the University of California San Diego lab in 2019.

Working closely with humans

Soft robots have some innate characteristics that make them better suited for certain industries or applications.

When combined with concepts like proximity sensing and force and torque limiting, a robot is better able to determine its distance to a human, and controllers reduce the operating speed and torque of the robot in turn. If there is incidental or accidental contact between the robot and the human, there is unlikely to be any injury. If the robot is made of supple elastomer materials, compressible foams or soft fabrics, this contact is even more likely to be brushed off by the relatively fragile human being.

This means that robots made of soft materials are optimal for scenarios where the robot and a human may occupy the same zone, including the factory floor. These "cobots" can be working right along with the human or may learn their activities from a human who hand-guides the robot through its task. These robots also excel in applications that require smooth touches such as rehabilitation, agricultural and medical robots.

Human-machine interaction between robots and people becomes safer and more natural with low force output and flexible materials that can cushion impacts. However, while soft robots are well adapted to some situations, they cannot replace conventional robots in every case.

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Reduced manufacturing and maintenance costs

Soft robots are often more susceptible to damage than their rigid counterparts due to fatigue from repetitive movements, interfacial debonding, perforations or overloading. While soft robots are resilient to impacts, they are also highly susceptible to damage from sharp objects. As their exterior surfaces consist of deformable material, microcracks resulting from cyclic loading occur more readily.

As a result, there is ample research into materials that self-heal (SH). SH robots can employ autonomous or non-autonomous systems. Autonomous SH systems require no added stimulus, whereas non-autonomous systems require intervention to heal, typically as heat, light, chemical or mechanical.

Extrinsically SH polymers do not contain a healing agent in the original material but require a healing agent to be applied to the material often via microcapsules or through a vascular system. On the other hand, intrinsically SH materials can recover from damage due to their own chemical properties.

For extrinsic systems, reactive chemical reagents are often stored throughout the material in microcapsules, and recently nanocapsules. The smaller nanocapsules increase the level of dispersion in the material. This mechanism is often used to facilitate healing of microcracks. However, the amount of healing possible is finite as once the capsules break the healing agent is consumed. More severe damage usually requires a vascular system connected to a reservoir with the healing agent, which may be able to provide healing properties longer term.

Intrinsic SH polymers have a potentially limitless ability to heal from damage. Many of these polymers gain their healing ability from dynamic covalent interactions. These bonds are reversible and can break and reform. These SH polymers are used as crosslinks in a polymer network, where low density networks are flexible and have elastomeric properties.

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Futuristic soft robot materials

Soft robots are predominantly manufactured using lithography and molding techniques, as well as via casting. Additive manufacturing is a manufacturing method that is recently being used in soft robotics and could be pivotal in making SH robots a commercial success. Elastomeric DA networks are rapidly being applied to SH robots using additive manufacturing.

Researchers have recently developed a hydrogel material that can heal at room temperature. Hydrogels are crosslinked polymer networks with higher water content. These materials are also biodegradable and can be 3D printed. This material is widely available, is stable long term and does not dry out. This hydrogel has not yet been applied to a commercial application but has working prototypes.

Soft sensors are a key component to soft robotics, similar to how the nervous system communicates with the brain about the current state of the body. Sensors can be built with salt instead of carbon ink, since salt is soluble in water-based hydrogels. This allows for a conductive channel to facilitate communication of the sensors. The salt allows for stretches to be sensed as well as electrical resistance changes in strain, which had a largely linear relationship.

There is the potential that robots manufactured of hydrogel materials and equipped with salt-based pseudo-sensors will be able to grasp fragile objects that can be a challenge for traditional rigid robots, like glass components. The same technology can provide a new means of locomotion for walking or swimming robots, potentially enabling new possibilities in the world of manufacturing.

Inspired by nature, with an ability to heal and “feel”

Innovations in soft robotics are heavily bio-inspired. With further development of sensors and materials, soft robots could react appropriately to “pain” and sense microscopic and macroscopic damage. Then, the system would react to restore all functionality to the damaged components. If soft robots were able to detect when injury was occurring, they would be able to stop the damage-inducing action and respond with artificial intelligence and machine-learning adapted techniques.

References

Hardman, D., George Thuruthel, T., & Iida, F. (2022, February 18). Self-healing ionic gelatin/glycerol hydrogels for strain sensing applications. NPG Asia Materials, 14(1). https://doi.org/10.1038/s41427-022-00357-9

Novikov, A. S. (2022, May 31). Self-Healing Polymers. Polymers, 14(11), 2261. https://doi.org/10.3390/polym14112261

Wang, T., Fan, X., Koh, J. J., He, C., & Yeow, C. H. (2022, August 30). Self-Healing Approach toward Catalytic Soft Robots. ACS Applied Materials &Amp; Interfaces, 14(36), 40590–40598. https://doi.org/10.1021/acsami.2c09889

Zhang, M. Q., & Rong, M. Z. (2022, April 19). Extrinsic and Intrinsic Approaches to Self-Healing Polymers and Polymer Composites (1st ed.). Wiley.

About the author

Jody Dascalu is a freelance writer in the technology and engineering niche. She studied in Canada and earned a Bachelor of Engineering. Jody has over five years of progressive supply chain work experience and is a business analyst. As an avid reader, she loves to research upcoming technologies and is an expert on a variety of topics.