Physical Reservoir Computing with Origami and its Application to Robotic Crawling
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Abstract (arXiv)
A new paradigm called physical reservoir computing has recently emerged, where the nonlinear dynamics of high-dimensional and fixed physical systems are harnessed as a computational resource to achieve complex tasks. Via extensive simulations based on a dynamic truss-frame model, this study shows that an origami structure can perform as a dynamic reservoir with sufficient computing power to emulate high-order nonlinear systems, generate stable limit cycles, and modulate outputs according to dynamic inputs. This study also uncovers the linkages between the origami reservoir's physical designs and its computing power, offering a guideline to optimize the computing performance. Comprehensive parametric studies show that selecting optimal feedback crease distribution and fine-tuning the underlying origami folding designs are the most effective approach to improve computing performance. Furthermore, this study shows how origami's physical reservoir computing power can apply to soft robotic control problems by a case study of earthworm-like peristaltic crawling without traditional controllers. These results can pave the way for origami-based robots with embodied mechanical intelligence.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Jan 2021.
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Citing papers per year: 2023: 3; 2024: 1; 2025: 2; 2026: 2.
8 papers.
- 2023A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learningcited by 22
- 2023Building Intelligence in the Mechanical Domain -- Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Taskscited by 2
- 2025Multifunctional physical reservoir computing in soft tensegrity robotscited by 2
- 2023Uncovering multifunctional mechano-intelligence in and through phononic metastructures harnessing physical reservoir computingcited by 0
- 2024Predicting unobserved climate time series data at distant areas via spatial correlation using reservoir computingcited by 0
- 2025Exoplanetary atmospheres retrieval via a quantum extreme learning machinecited by 0
- 2026OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computingcited by 0
- 2026On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classificationcited by 0
- 2026On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification23 Apr 2026
- 2026OpenPRC: A Unified Open-Source Framework for Physics-to-Task Evaluation in Physical Reservoir Computing8 Apr 2026
- 2025Exoplanetary atmospheres retrieval via a quantum extreme learning machine3 Sep 2025
- 2025Multifunctional physical reservoir computing in soft tensegrity robots29 Jul 2025
- 2024Predicting unobserved climate time series data at distant areas via spatial correlation using reservoir computing5 Jun 2024
- 2023A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learning27 Jul 2023
- 2023Uncovering multifunctional mechano-intelligence in and through phononic metastructures harnessing physical reservoir computing30 May 2023
- 2023Building Intelligence in the Mechanical Domain -- Harvesting the Reservoir Computing Power in Origami to Achieve Information Perception Tasks10 Feb 2023