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Bubble casting soft robotics

Author

Listed:
  • Trevor J. Jones

    (Princeton University)

  • Etienne Jambon-Puillet

    (Princeton University)

  • Joel Marthelot

    (Princeton University
    Aix-Marseille University, CNRS, IUSTI)

  • P.-T. Brun

    (Princeton University)

Abstract

Inspired by living organisms, soft robots are developed from intrinsically compliant materials, enabling continuous motions that mimic animal and vegetal movement1. In soft robots, the canonical hinges and bolts are replaced by elastomers assembled into actuators programmed to change shape following the application of stimuli, for example pneumatic inflation2–5. The morphing information is typically directly embedded within the shape of these actuators, whose assembly is facilitated by recent advances in rapid prototyping techniques6–11. 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, for example 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, for example long, tortuous or vascular structures, thereby paving the way towards new functionalities stemming from geometric and material nonlinearities.

Suggested Citation

  • Trevor J. Jones & Etienne Jambon-Puillet & Joel Marthelot & P.-T. Brun, 2021. "Bubble casting soft robotics," Nature, Nature, vol. 599(7884), pages 229-233, November.
  • Handle: RePEc:nat:nature:v:599:y:2021:i:7884:d:10.1038_s41586-021-04029-6
    DOI: 10.1038/s41586-021-04029-6
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    Citations

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    Cited by:

    1. Alejandro Martínez-Calvo & Matthew D. Biviano & Anneline H. Christensen & Eleni Katifori & Kaare H. Jensen & Miguel Ruiz-García, 2024. "The fluidic memristor as a collective phenomenon in elastohydrodynamic networks," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    2. Jiefeng Sun & Elisha Lerner & Brandon Tighe & Clint Middlemist & Jianguo Zhao, 2023. "Embedded shape morphing for morphologically adaptive robots," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Dongliang Fan & Xi Yuan & Wenyu Wu & Renjie Zhu & Xin Yang & Yuxuan Liao & Yunteng Ma & Chufan Xiao & Cheng Chen & Changyue Liu & Hongqiang Wang & Peiwu Qin, 2022. "Self-shrinking soft demoulding for complex high-aspect-ratio microchannels," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    4. Jun Kyu Choe & Junsoo Kim & Hyeonseo Song & Joonbum Bae & Jiyun Kim, 2023. "A soft, self-sensing tensile valve for perceptive soft robots," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    5. Liang Yue & S. Macrae Montgomery & Xiaohao Sun & Luxia Yu & Yuyang Song & Tsuyoshi Nomura & Masato Tanaka & H. Jerry Qi, 2023. "Single-vat single-cure grayscale digital light processing 3D printing of materials with large property difference and high stretchability," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    6. Jiang Yan & Ying Zhang & Zongguang Liu & Junzhuan Wang & Jun Xu & Linwei Yu, 2023. "Ultracompact single-nanowire-morphed grippers driven by vectorial Lorentz forces for dexterous robotic manipulations," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    7. Man Hu & Feng Wang & Li Chen & Peng Huo & Yuqi Li & Xi Gu & Kai Leong Chong & Daosheng Deng, 2022. "Near-infrared-laser-navigated dancing bubble within water via a thermally conductive interface," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    8. Shibo Zou & Sergio Picella & Jelle Vries & Vera G. Kortman & Aimée Sakes & Johannes T. B. Overvelde, 2024. "A retrofit sensing strategy for soft fluidic robots," Nature Communications, Nature, vol. 15(1), pages 1-12, December.
    9. Wenfei Ai & Kai Hou & Jiaxin Wu & Yue Long & Kai Song, 2024. "Miniaturized and untethered McKibben muscles based on photothermal-induced gas-liquid transformation," Nature Communications, Nature, vol. 15(1), pages 1-8, December.

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