Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators
This paper presents robust, repeatable, and scalable fabrication procedures for soft pneumatic actuators using two-part silicone pour casting, including methods to prevent internal cavity clogging and ensure airtight sealing, as well as a robust sensor embedding procedure for thin-film flex sensors. Finite Element Modeling, PID-controlled pneumatic experiments, and automated image processing calibration validate the actuator performance. Staircase and sinusoidal actuation tests demonstrate high repeatability and low hysteresis, validated across two operators and 24 successful fabrications.
-->
[Submitted on 16 Jul 2026]
Title:Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators
View a PDF of the paper titled Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators, by Harshit Thakker and 3 other authors
View PDF
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.
Comments: 8 pages, 17 figures, to be published in: IEEE RAS/EMBS 11th International Conference on Biomedical Robotics and Biomechatronics (BioRob 2026)
Subjects:
Robotics (cs.RO)
Cite as: arXiv:2607.15422 [cs.RO]
(or arXiv:2607.15422v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2607.15422
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Jacqueline Libby [view email] [v1] Thu, 16 Jul 2026 19:53:33 UTC (2,913 KB)
Full-text links:
Access Paper:
View a PDF of the paper titled Robust Silicone Pour Casting and Sensor Embedding Procedures for Soft Robotic Actuators, by Harshit Thakker and 3 other authors
View PDF
TeX Source
view license
Current browse context:
cs.RO
new | recent | 2026-07
Change to browse by:
cs
References & Citations
NASA ADS
Google Scholar
Semantic Scholar
Loading...
Data provided by:
Bibliographic Tools
Bibliographic and Citation Tools
Bibliographic Explorer Toggle
Bibliographic Explorer (What is the Explorer?)
Connected Papers Toggle
Connected Papers (What is Connected Papers?)
Litmaps Toggle
Litmaps (What is Litmaps?)
scite.ai Toggle
scite Smart Citations (What are Smart Citations?)
Code, Data, Media
Code, Data and Media Associated with this Article
alphaXiv Toggle
alphaXiv (What is alphaXiv?)
Links to Code Toggle
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub Toggle
DagsHub (What is DagsHub?)
GotitPub Toggle
Gotit.pub (What is GotitPub?)
Huggingface Toggle
Hugging Face (What is Huggingface?)
ScienceCast Toggle
ScienceCast (What is ScienceCast?)
Demos
Demos
Replicate Toggle
Replicate (What is Replicate?)
Spaces Toggle
Hugging Face Spaces (What is Spaces?)
Spaces Toggle
TXYZ.AI (What is TXYZ.AI?)
Related Papers
Recommenders and Search Tools
Link to Influence Flower
Influence Flower (What are Influence Flowers?)
Core recommender toggle
CORE Recommender (What is CORE?)
Author
Venue
Institution
Topic
About arXivLabs
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)