Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing
Abstract
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.
Keywords
Cite
@article{arxiv.2511.23215,
title = {Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing},
author = {Eduardo Sergio Oliveros-Mata and Oleksandr V. Pylypovskyi and Eleonora Raimondo and Rico Illing and Yevhen Zabila and Lin Guo and Guannan Mu and Mónica Navarro López and Xu Wang and Georgios Tzortzinis and Angelos Filippatos and Gilbert Santiago Cañón Bermúdez and Francesca Garescì and Giovanni Finocchio and Denys Makarov},
journal= {arXiv preprint arXiv:2511.23215},
year = {2025}
}