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

arXiv: https://arxiv.org/abs/2302.05517 · HTML: https://mlsanity.com/paper/2302.05517/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 52 references that are in the map.
- First posted on arXiv 10 Feb 2023.

## Builds on (most cited first, 7 of 7)

- [Physical reservoir computing -- An introductory perspective](https://mlsanity.com/paper/2005.00992/) (2020)
- [Role of non-linear data processing on speech recognition task in the framework of reservoir computing](https://mlsanity.com/paper/1906.02812/) (2019)
- [Physical Reservoir Computing with Origami and its Application to Robotic Crawling](https://mlsanity.com/paper/2101.08348/) (2021)
- [Adaptive model selection in photonic reservoir computing by reinforcement learning](https://mlsanity.com/paper/2004.12575/) (2020)
- [Distributed Machine Learning in Materials that Couple Sensing, Actuation, Computation and Communication](https://mlsanity.com/paper/1606.03508/) (2016)
- [Peristaltic locomotion without digital controllers: Exploiting the origami multi-stability to coordinate robotic motions](https://mlsanity.com/paper/1906.04091/) (2019)
- [Harnessing The Multi-Stability Of Kresling Origami For Reconfigurable Articulation In Soft Robotic Arms](https://mlsanity.com/paper/2008.07421/) (2020)

## Built on by (most cited first, 2 of 2)

- [Multifunctional physical reservoir computing in soft tensegrity robots](https://mlsanity.com/paper/2507.21496/) (2025)
- [Uncovering multifunctional mechano-intelligence in and through phononic metastructures harnessing physical reservoir computing](https://mlsanity.com/paper/2305.19354/) (2023)

## Abstract (arXiv)

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.