Bubble casting soft robotics

Trevor Jones (1) , Etienne Jambon-Puillet (1) , Joel Marthelot (2) , P.-T. Brun (1)

1 Princeton University
2 IUSTI - Institut universitaire des systèmes thermiques industriels

Inspired by living organisms, soft robots are developed from intrinsically compliant materials enabling con- tinuous motions mimicking animal and vegetal movement. In soft robots, the canonical hinges and bolts are replaced by elastomers assembled into actuators programmed to change shape following the application of stimuli, e.g. pneumatic inflation. The morphing information is typically directly embedded within the shape of these actuators, whose assembly is facilitated by recent advances in rapid prototyping techniques. Yet, these manufacturing processes have limitations in scalability, design flexibility and robustness. Here we demonstrate a new all-in-one methodology for the fabrication and the programming of soft machines. Instead of relying on the assembly of individual parts, our approach harnesses interfacial flows in elastomers that progressively cure to robustly produce monolithic pneumatic actuators whose shape can easily be tailored to suit applications ranging from artificial muscles to grippers. We rationalize the fluid mechanics at play in the assembly of our actuators and model their subsequent morphing. We leverage this quantitative knowledge to program these soft machines and produce complex functionalities, e.g. sequential motion obtained from a monotonic stimulus. We expect that the flexibility, robustness and predictive nature of our methodology will accelerate the proliferation of soft robotics by enabling the assembly of complex actuators, e.g. long, tortuous or vascular structures, thereby paving the way towards new functionalities stemming from geometric and material nonlinearities.

Domaines: Mécanique des fluides [physics.class-ph]; Mécanique des solides [physics.class-ph]; Matière Molle [cond-mat.soft]

Trevor Jones, Etienne Jambon-Puillet, Joel Marthelot, P.-T. Brun. Bubble casting soft robotics. Nature, 2021, 599 (7884), pp.229-233. ⟨10.1038/s41586-021-04029-6⟩. ⟨hal-03449691⟩