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In robotics, achieving adaptivity in complex environments is challenging. Traditional robotic systems use stiff materials and computationally expensive centralized controllers, while nature often favors soft materials and embodied intelligence. Inspired by nature's distributed intelligence, this study explores a decentralized approach for robust behavior in soft robotic systems without knowledge of their shape or environment. It is demonstrated that only a few basic rules implemented in identical modules that shape the soft robotic system can enable whole-body phototaxis, navigating on a surface toward a light source, without explicit communication between modules or prior system knowledge. The results reveal the method's effectiveness in generating robust and adaptive behavior in dynamic and challenging environments. Moreover, the approach's simplicity makes it possible to illustrate and understand the underlying mechanism of the observed behavior, paying particular attention to the geometry of the assembled system and the effect of learning parameters. Consequently, the findings offer insights into the development of adaptive, autonomous robotic systems with minimal computational power, paving the way for robust and useful behavior in soft and microscale robots, as well as robotic matter, that operate in real-worldenvironments.
Originele taal-2 | Engels |
---|---|
Artikelnummer | 2310932 |
Tijdschrift | Advanced Functional Materials |
Volume | XX |
Nummer van het tijdschrift | X |
DOI's | |
Status | Geaccepteerd/In druk - 29 mei 2024 |
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Schomaker, H. A. H., Picella, S., Küng Garcia, A., van Laake, L. C. (Geaccepteerd/In druk). Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems. Advanced Functional Materials, XX(X), Artikel 2310932. https://doi.org/10.1002/adfm.202310932
Schomaker, H.A.H. ; Picella, S. ; Küng Garcia, A. et al. / Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems. In: Advanced Functional Materials. 2024 ; Vol. XX, Nr. X.
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title = "Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems",
abstract = "In robotics, achieving adaptivity in complex environments is challenging. Traditional robotic systems use stiff materials and computationally expensive centralized controllers, while nature often favors soft materials and embodied intelligence. Inspired by nature's distributed intelligence, this study explores a decentralized approach for robust behavior in soft robotic systems without knowledge of their shape or environment. It is demonstrated that only a few basic rules implemented in identical modules that shape the soft robotic system can enable whole-body phototaxis, navigating on a surface toward a light source, without explicit communication between modules or prior system knowledge. The results reveal the method's effectiveness in generating robust and adaptive behavior in dynamic and challenging environments. Moreover, the approach's simplicity makes it possible to illustrate and understand the underlying mechanism of the observed behavior, paying particular attention to the geometry of the assembled system and the effect of learning parameters. Consequently, the findings offer insights into the development of adaptive, autonomous robotic systems with minimal computational power, paving the way for robust and useful behavior in soft and microscale robots, as well as robotic matter, that operate in real-worldenvironments.",
keywords = "decentralized, embodied learning, phototaxis, physical intelligence, robotic matter",
author = "H.A.H. Schomaker and S. Picella and {K{\"u}ng Garcia}, A. and {van Laake}, L.C. and J.T.B. Overvelde",
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Schomaker, HAH, Picella, S, Küng Garcia, A, van Laake, LC 2024, 'Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems', Advanced Functional Materials, vol. XX, nr. X, 2310932. https://doi.org/10.1002/adfm.202310932
Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems. / Schomaker, H.A.H.; Picella, S.; Küng Garcia, A. et al.
In: Advanced Functional Materials, Vol. XX, Nr. X, 2310932, 29.05.2024.
Onderzoeksoutput: Bijdrage aan tijdschrift › Tijdschriftartikel › Academic › peer review
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T1 - Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems
AU - Schomaker, H.A.H.
AU - Picella, S.
AU - Küng Garcia, A.
AU - van Laake, L.C.
AU - Overvelde, J.T.B.
PY - 2024/5/29
Y1 - 2024/5/29
N2 - In robotics, achieving adaptivity in complex environments is challenging. Traditional robotic systems use stiff materials and computationally expensive centralized controllers, while nature often favors soft materials and embodied intelligence. Inspired by nature's distributed intelligence, this study explores a decentralized approach for robust behavior in soft robotic systems without knowledge of their shape or environment. It is demonstrated that only a few basic rules implemented in identical modules that shape the soft robotic system can enable whole-body phototaxis, navigating on a surface toward a light source, without explicit communication between modules or prior system knowledge. The results reveal the method's effectiveness in generating robust and adaptive behavior in dynamic and challenging environments. Moreover, the approach's simplicity makes it possible to illustrate and understand the underlying mechanism of the observed behavior, paying particular attention to the geometry of the assembled system and the effect of learning parameters. Consequently, the findings offer insights into the development of adaptive, autonomous robotic systems with minimal computational power, paving the way for robust and useful behavior in soft and microscale robots, as well as robotic matter, that operate in real-worldenvironments.
AB - In robotics, achieving adaptivity in complex environments is challenging. Traditional robotic systems use stiff materials and computationally expensive centralized controllers, while nature often favors soft materials and embodied intelligence. Inspired by nature's distributed intelligence, this study explores a decentralized approach for robust behavior in soft robotic systems without knowledge of their shape or environment. It is demonstrated that only a few basic rules implemented in identical modules that shape the soft robotic system can enable whole-body phototaxis, navigating on a surface toward a light source, without explicit communication between modules or prior system knowledge. The results reveal the method's effectiveness in generating robust and adaptive behavior in dynamic and challenging environments. Moreover, the approach's simplicity makes it possible to illustrate and understand the underlying mechanism of the observed behavior, paying particular attention to the geometry of the assembled system and the effect of learning parameters. Consequently, the findings offer insights into the development of adaptive, autonomous robotic systems with minimal computational power, paving the way for robust and useful behavior in soft and microscale robots, as well as robotic matter, that operate in real-worldenvironments.
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Schomaker HAH, Picella S, Küng Garcia A, van Laake LC, Overvelde JTB. Robust Phototaxis by Harnessing Implicit Communication in Modular Soft Robotic Systems. Advanced Functional Materials. 2024 mei 29;XX(X):2310932. doi: 10.1002/adfm.202310932