Building Intelligence in the Mechanical Domain -- Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks
This work addresses the problem of integrating intelligence into mechanical systems like deployable structures and robots, offering a novel approach but with incremental impact as it builds on existing reservoir computing frameworks.
The paper tackled the problem of enabling information perception in mechanical structures by experimentally demonstrating that a paper-based Miura-ori origami, used as a physical reservoir computing resource, can estimate payload weight and position, recognize input frequency and magnitude patterns, and perform multitasking through linear regression training. The result showed that the origami reservoir has sufficient computing capacity for these tasks, adding a new dimension to the functionality of such structures.
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.