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We investigate the controllability of an origami system composed of Miura-ori cells. A substantial volume of research on folding architecture, kinematic behavior, and actuation techniques of origami structures has been conducted. However, understanding their transient dynamics and constructing control models remains a formidable task, primarily due to their innate flexibility and compliance. In light of this challenge, we discretize the origami system into a network composed of interconnected particle masses alongside bar and hinge elements. This yields a state-space representation of the system's dynamics, enabling us to obtain the system's controllability attributes. Informed by this computational framework, we explore the controllability Gramian-based method for finding the most efficient crease line for Miura-ori cell deployment using an actuator. We demonstrate that the deployment efficiency guided by this theoretical method agrees with the empirical results obtained from the energy consumption to deploy the origami structure. This investigation paves the way toward designing and operating an efficient the complex actuation system for origami tessellations.
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Building Intelligence in the Mechanical Domain—Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks
Herein, the cognitive capability of a simple, paper‐based Miura‐ori—using the physical reservoir computing framework—is experimentally examined 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, it is shown 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, it is demonstrated 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.
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- Award ID(s):
- 2239673
- PAR ID:
- 10441357
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Advanced Intelligent Systems
- Volume:
- 5
- Issue:
- 9
- ISSN:
- 2640-4567
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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