Building Intelligence in the Mechanical Domain -- Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks

TL;DR

This paper demonstrates that a simple paper-based Miura-ori origami structure can function as a physical reservoir computer, enabling it to perform various information perception tasks such as estimating payloads and recognizing input patterns.

Contribution

The study introduces a novel application of origami structures as physical reservoirs for computational tasks, expanding their functional capabilities beyond traditional uses.

Findings

Miura-ori can estimate payload weight and position.

It can recognize input frequency and magnitude patterns.

Multitasking is achievable with the same reservoir.

Abstract

In this paper, we experimentally examine the cognitive capability of a simple, paper-based Miura-ori -- using the physical reservoir computing framework -- to achieve different information perception tasks. The body dynamics of Miura-ori (aka. its vertices displacements), which is excited by a simple harmonic base excitation, can be exploited as the reservoir computing resource. By recording these dynamics with a high-resolution camera and image processing program and then using linear regression for training, we show that the origami reservoir has sufficient computing capacity to estimate the weight and position of a payload. It can also recognize the input frequency and magnitude patterns. Furthermore, multitasking is achievable by simultaneously applying two targeted functions to the same reservoir state matrix. Therefore, we demonstrate that Miura-ori can assess the dynamic interactions between its body and ambient environment to extract meaningful information -- an intelligent behavior in the mechanical domain. Given that Miura-ori has been widely used to construct deployable structures, lightweight materials, and compliant robots, enabling such information perception tasks can add a new dimension to the functionality of such a versatile structure.