Manufacturing soft robots with an innovative automated process

Commercial-scale production of customised soft robots may be attainable in the near future due to the development of a novel automated approach.

The method, developed by researchers from the Singapore University of Technology and Design (SUTD), has achieved this monumental feat by amalgamating two distinct approaches into one integrated workflow. Their new automated process enables them to design, and construct customised soft robots efficiently. The technique is also viable for application on other types of soft robots, allowing mechanical components to be tailored in an accessible manner.

Their research is published in the journal Advanced Materials.

Rewriting the blueprints for soft robots

Traditionally, robots are portrayed as rigid, clunky, metallic structures, used primarily for their durability, not their malleability. However, a new generation of robotics looks to break that stigma, with pliable soft robots garnering considerable popularity and attention in recent years, sparking the imagination of engineers worldwide of what their potential applications could be.

The flexibility demonstrated by living organisms inspired the inception of soft robots, with them having a wide range of potential purposes in movement, sensing, and object grasping and manipulation. Despite this versatility, currently used methods for manufacturing soft robots remain rudimentary, with conventional manual casting techniques being limited in the complexities and geometries that can be produced in soft robots.

Pablo Valdivia y Alvarado, the leader of the study and an assistant professor at SUTD, said: “Most fabrication approaches are predominantly manual due to a lack of standard tools. But 3D printing or additive manufacturing is slowly coming into play as it facilitates repeatability and allows more complex designs, improving quality, and performance.”

Designing an integrated workflow

The researchers explained that embedded 3D printing – where multiple material inks are extruded in a supportive matrix – is the ideal method for manufacturing soft robots comprised of numerous materials or composites. To ensure that these robots are designed optimally, the team employed topology optimisation (TO), which uses mathematical models to blueprint unique structures within a set of constraints.

By automating these two vital steps into one singular framework, the team created an integrated workflow for developing customised soft robots and mitigated possible errors along the way. The team employed a batoid inspired, swimming autonomous robot for their investigation, with the workflow starting by defining the robot’s fin geometry, with TO utilised to produce the desired structure with ideal properties within prescribed material and motion constraints. This optimal design is then converted into a code that is interpreted by custom-built 3D printers that subsequently build the robot.

Assessing performance

The specialised soft robots were constructed to survive the harsh conditions of a marine environment, with a considerable focus being on designing their fin composition and examining how these alterations could affect the soft robot’s swimming performance. The researchers devised three types of fins – two fabricated from soft and stiff materials and a third designed from a combination of the two using TO – with the third composite fin following the integrated workflow, whereas the others did not.

The soft robot with the composite fins astoundingly achieved a 50% speed increase compared to the conventionally casted soft fin and was marginally faster than the hard fin, also changing direction 30% quicker than the soft fin, demonstrating the smallest turning radius of the three robots, displaying is proficiency in manoeuvring through the water.

After demonstrating the performance of their technique, the researchers are confident that their workflow for fabricating optimised, multi-material soft robots can be used to design an array of robotics

“For example, if we’re building a sensor, our objective in TO could be to tailor the electrical conductivity of certain portions of the structure,” said Dr Valdivia y Alvarado. “Customising optical, thermal, electrical, as well as other physico-chemical properties would also be interesting for other applications.”

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