Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866917111703535616 |
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| author | Oliveros-Mata, Eduardo Sergio Pylypovskyi, Oleksandr V. Raimondo, Eleonora Illing, Rico Zabila, Yevhen Guo, Lin Mu, Guannan López, Mónica Navarro Wang, Xu Tzortzinis, Georgios Filippatos, Angelos Bermúdez, Gilbert Santiago Cañón Garescì, Francesca Finocchio, Giovanni Makarov, Denys |
| author_facet | Oliveros-Mata, Eduardo Sergio Pylypovskyi, Oleksandr V. Raimondo, Eleonora Illing, Rico Zabila, Yevhen Guo, Lin Mu, Guannan López, Mónica Navarro Wang, Xu Tzortzinis, Georgios Filippatos, Angelos Bermúdez, Gilbert Santiago Cañón Garescì, Francesca Finocchio, Giovanni Makarov, Denys |
| contents | Complex and even chaotic dynamics, though prevalent in many natural and engineered systems, has been largely avoided in the design of electromechanical systems due to concerns about wear and controlability. Here, we demonstrate that complex dynamics might be particularly advantageous in soft robotics, offering new functionalities beyond motion not easily achievable with traditional actuation methods. We designed and realized resilient magnetic soft actuators capable of operating in a tunable dynamic regime for tens of thousands cycles without fatigue. We experimentally demonstrated the application of these actuators for true random number generation and stochastic computing. {W}e validate soft robots as physical reservoirs capable of performing Mackey--Glass time series prediction. These findings show that exploring the complex dynamics in soft robotics would extend the application scenarios in soft computing, human-robot interaction and collaborative robots as we demonstrate with biomimetic blinking and randomized voice modulation. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_23215 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing Oliveros-Mata, Eduardo Sergio Pylypovskyi, Oleksandr V. Raimondo, Eleonora Illing, Rico Zabila, Yevhen Guo, Lin Mu, Guannan López, Mónica Navarro Wang, Xu Tzortzinis, Georgios Filippatos, Angelos Bermúdez, Gilbert Santiago Cañón Garescì, Francesca Finocchio, Giovanni Makarov, Denys Robotics Other Condensed Matter Strongly Correlated Electrons Complex and even chaotic dynamics, though prevalent in many natural and engineered systems, has been largely avoided in the design of electromechanical systems due to concerns about wear and controlability. Here, we demonstrate that complex dynamics might be particularly advantageous in soft robotics, offering new functionalities beyond motion not easily achievable with traditional actuation methods. We designed and realized resilient magnetic soft actuators capable of operating in a tunable dynamic regime for tens of thousands cycles without fatigue. We experimentally demonstrated the application of these actuators for true random number generation and stochastic computing. {W}e validate soft robots as physical reservoirs capable of performing Mackey--Glass time series prediction. These findings show that exploring the complex dynamics in soft robotics would extend the application scenarios in soft computing, human-robot interaction and collaborative robots as we demonstrate with biomimetic blinking and randomized voice modulation. |
| title | Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing |
| topic | Robotics Other Condensed Matter Strongly Correlated Electrons |
| url | https://arxiv.org/abs/2511.23215 |