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Modular force approximating soft robotic pneumatic actuator

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Soft robots are highly flexible and adaptable instruments that have proven extremely useful, especially in the surgical environment where compliance allows for improved maneuverability throughout the body. Endoscopic devices are a primary example of an instrument that physicians use to navigate to difficult-to-reach areas inside the body. This paper presents a modular soft robotic pneumatic actuator as a proof of concept for a compliant endoscopic device.

Methods

The actuator is 3D printed using an FDM printer. Maximum bending angle is measured using image processing in MATLAB at a gauge pressure level of 35 psi. End-effector displacement is measured using electromagnetic tracking as gauge pressure ranges from 10 to 35 psi, and uniaxial tensile loading ranges from 0 to 120 g.

Results

The actuator achieves a maximum bending angle of 145°. Fourth-order polynomial regression is used to model the actuator displacement upon inflation and tensile loading with an average coefficient of correlation value of 0.998. We also develop a feedforward neural network as a robust computer-assisted method for controlling the actuator that achieves a coefficient of correlation value of 0.996.

Conclusion

We propose a novel modular soft robotic pneumatic actuator that is developed via rapid prototyping and evaluated using image processing and machine learning models. The curled resting shape allows for simple manufacturing and achieves a greater range of bending than other actuators of its kind. A feedforward neural network provides accurate prediction of end-effector displacement upon inflation and loading to deliver precise manipulation and control.

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Acknowledgments

This study was supported in part by the National Institutes of Health (NIH) Bench-to-Bedside Award, the NIH Center for Interventional Oncology Grant, the National Science Foundation (NSF) I-Corps Team Grant (1617340), NSF REU site program 1359095, the UGA-AU Inter-Institutional Seed Funding, the American Society for Quality Dr. Richard J. Schlesinger Grant, the PHS Grant UL1TR000454 from the Clinical and Translational Science Award Program, and the NIH National Center for Advancing Translational Sciences.

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Authors and Affiliations

  1. School of Electrical and Computer Engineering, The University of Georgia, 597 DW Brooks Dr., Athens, GA, 30602, USA

    Austin J. Taylor, Rudy Montayre, Zhuo Zhao & Zion Tsz Ho Tse

  2. Department of Mechanical Engineering, The University of Hong Kong, Pokfulam, Hong Kong, China

    Ka Wai Kwok

Authors
  1. Austin J. Taylor
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  2. Rudy Montayre
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  3. Zhuo Zhao
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  4. Ka Wai Kwok
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  5. Zion Tsz Ho Tse
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Corresponding author

Correspondence to Zion Tsz Ho Tse.

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The authors declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Taylor, A.J., Montayre, R., Zhao, Z. et al. Modular force approximating soft robotic pneumatic actuator. Int J CARS 13, 1819–1827 (2018). https://doi.org/10.1007/s11548-018-1833-4

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  • DOI: https://doi.org/10.1007/s11548-018-1833-4

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