Self-vectoring electromagnetic soft robots with high operational dimensionality
Wenbo Li (),
Huyue Chen,
Zhiran Yi,
Fuyi Fang,
Xinyu Guo,
Zhiyuan Wu,
Qiuhua Gao,
Lei Shao (),
Jian Xu,
Guang Meng and
Wenming Zhang ()
Additional contact information
Wenbo Li: Shanghai Jiao Tong University
Huyue Chen: University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University
Zhiran Yi: Shanghai Jiao Tong University
Fuyi Fang: Shanghai Jiao Tong University
Xinyu Guo: Shanghai Jiao Tong University
Zhiyuan Wu: Shanghai Jiao Tong University
Qiuhua Gao: Shanghai Jiao Tong University
Lei Shao: University of Michigan–Shanghai Jiao Tong University Joint Institute, Shanghai Jiao Tong University
Jian Xu: Tongji University
Guang Meng: Shanghai Jiao Tong University
Wenming Zhang: Shanghai Jiao Tong University
Nature Communications, 2023, vol. 14, issue 1, 1-13
Abstract:
Abstract Soft robots capable of flexible deformations and agile locomotion similar to biological systems are highly desirable for promising applications, including safe human-robot interactions and biomedical engineering. Their achievable degree of freedom and motional deftness are limited by the actuation modes and controllable dimensions of constituent soft actuators. Here, we report self-vectoring electromagnetic soft robots (SESRs) to offer new operational dimensionality via actively and instantly adjusting and synthesizing the interior electromagnetic vectors (EVs) in every flux actuator sub-domain of the robots. As a result, we can achieve high-dimensional operation with fewer actuators and control signals than other actuation methods. We also demonstrate complex and rapid 3D shape morphing, bioinspired multimodal locomotion, as well as fast switches among different locomotion modes all in passive magnetic fields. The intrinsic fast (re)programmability of SESRs, along with the active and selective actuation through self-vectoring control, significantly increases the operational dimensionality and possibilities for soft robots.
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-35848-y
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DOI: 10.1038/s41467-023-35848-y
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