Field-programmable dynamics in a soft magnetic actuator enabling true random number generation and reservoir computing

TL;DR

This paper introduces resilient magnetic soft actuators with tunable complex dynamics, enabling true random number generation and reservoir computing, thus expanding soft robotics applications into soft computing and human-robot interaction.

Contribution

The work demonstrates the design of durable magnetic soft actuators capable of complex dynamics and their application in true random number generation and reservoir computing.

Findings

Actuators operate in a tunable dynamic regime for tens of thousands of cycles without fatigue.

Successfully demonstrated true random number generation and stochastic computing.

Validated soft robots as physical reservoirs for time series prediction.

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.