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Mechanical computing

Author

Listed:
  • Hiromi Yasuda

    (University of Pennsylvania)

  • Philip R. Buskohl

    (Air Force Research Laboratory)

  • Andrew Gillman

    (Air Force Research Laboratory)

  • Todd D. Murphey

    (Northwestern University)

  • Susan Stepney

    (University of York)

  • Richard A. Vaia

    (Air Force Research Laboratory)

  • Jordan R. Raney

    (University of Pennsylvania)

Abstract

Mechanical mechanisms have been used to process information for millennia, with famous examples ranging from the Antikythera mechanism of the Ancient Greeks to the analytical machines of Charles Babbage. More recently, electronic forms of computation and information processing have overtaken these mechanical forms, owing to better potential for miniaturization and integration. However, several unconventional computing approaches have recently been introduced, which blend ideas of information processing, materials science and robotics. This has raised the possibility of new mechanical computing systems that augment traditional electronic computing by interacting with and adapting to their environment. Here we discuss the use of mechanical mechanisms, and associated nonlinearities, as a means of processing information, with a view towards a framework in which adaptable materials and structures act as a distributed information processing network, even enabling information processing to be viewed as a material property, alongside traditional material properties such as strength and stiffness. We focus on approaches to abstract digital logic in mechanical systems, discuss how these systems differ from traditional electronic computing, and highlight the challenges and opportunities that they present.

Suggested Citation

  • Hiromi Yasuda & Philip R. Buskohl & Andrew Gillman & Todd D. Murphey & Susan Stepney & Richard A. Vaia & Jordan R. Raney, 2021. "Mechanical computing," Nature, Nature, vol. 598(7879), pages 39-48, October.
    • Handle: RePEc:nat:nature:v:598:y:2021:i:7879:d:10.1038_s41586-021-03623-y
    DOI: 10.1038/s41586-021-03623-y
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    Citations

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    Cited by:

    1. Brigitta Dúzs & Oliver Skarsetz & Giorgio Fusi & Claudius Lupfer & Andreas Walther, 2024. "Mechano-adaptive meta-gels through synergistic chemical and physical information-processing," Nature Communications, Nature, vol. 15(1), pages 1-10, December.
    2. Tie Mei & Zhiqiang Meng & Kejie Zhao & Chang Qing Chen, 2021. "A mechanical metamaterial with reprogrammable logical functions," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    3. Tie Mei & Chang Qing Chen, 2023. "In-memory mechanical computing," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    4. Ahalya Prabhakar & Todd Murphey, 2022. "Mechanical intelligence for learning embodied sensor-object relationships," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    5. Junghwan Byun & Aniket Pal & Jongkuk Ko & Metin Sitti, 2024. "Integrated mechanical computing for autonomous soft machines," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    6. Zachary G. Nicolaou & Feng Jiang & Adilson E. Motter, 2024. "Metamaterials with negative compressibility highlight evolving interpretations and opportunities," Nature Communications, Nature, vol. 15(1), pages 1-3, December.
    7. Xin Zhou & Xingjing Ren & Dingbang Xiao & Jianqi Zhang & Ran Huang & Zhipeng Li & Xiaopeng Sun & Xuezhong Wu & Cheng-Wei Qiu & Franco Nori & Hui Jing, 2023. "Higher-order singularities in phase-tracked electromechanical oscillators," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    8. Wenzhong Yan & Shuguang Li & Mauricio Deguchi & Zhaoliang Zheng & Daniela Rus & Ankur Mehta, 2023. "Origami-based integration of robots that sense, decide, and respond," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    9. Florian Allein & Adamantios Anastasiadis & Rajesh Chaunsali & Ian Frankel & Nicholas Boechler & Fotios K. Diakonos & Georgios Theocharis, 2023. "Strain topological metamaterials and revealing hidden topology in higher-order coordinates," Nature Communications, Nature, vol. 14(1), pages 1-9, December.

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