Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators

Abstract:Soft robots are well-suited for applications such as rehabilitation and surgery that require adaptable and safe interaction with their environment. However, the challenges of reproducible and scalable fabrication of soft robots limit their real-world deployment. Various fabrication methods have been introduced, but many are labor-intensive and prone to human error. Therefore, traditional two-part pour casting remains an attractive option. This paper presents procedures for robust, repeatable, and scalable fabrication of soft pneumatic actuators using two-part pour casting. The presented methods prevent internal cavity clogging and ensure air-tight sealing. Additionally, a robust sensor embedding procedure for thin-film flex sensors is presented, which allows for accurate and repeatable data acquisition. Finite Element Modeling (FEM) of the soft actuator is performed to analyze stress and deformation from internal pressure loadings. Pneumatic actuation experiments with PID pressure control are performed. Automated image processing is used to calibrate the embedded flex sensor to bending angle measurements. Staircase and sinusoidal profile actuation experiments validate the performance of the fabricated actuator. Angle response experiments for the staircase input show repeatable performance, and the sinusoidal input shows a small amount of hysteresis consistent with viscoelastic response to pneumatic actuation of soft actuators. Simulated and real-world bending angles show comparable response. These methods provide a repeatable and robust fabrication procedure, validated across two operators and 24 successful fabrications, along with benchmark simulations and experimental testing. These benchmarks will enable more widespread adoption of soft robotics.

Robotics (cs.RO)

arXiv:2607.15422 [cs.RO]

(or arXiv:2607.15422v1 [cs.RO] for this version)

https://doi.org/10.48550/arXiv.2607.15422 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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