A foldable small-scale soft electromagnetic robot for multimodal navigation in confined and unstructured environments

Multimodal locomotion is crucial for an animal’s adaptability in unstructured wild environments. Analogously, in the human gastrointestinal tract, characterized by viscoelastic mucus, complex rugae, and narrow openings like the cardia, multimodal locomotion is also essential for a small-scale soft robot to conduct tasks. Here, we introduce a small-scale, compact, foldable, and robust soft electromagnetic robot with more than nine locomotion modes designed for such a scenario. Featuring a six-spoke elastomer body embedded with liquid metal channels and driven by Laplace forces under a static magnetic field, the robot is capable of rapid transitions ( < 0.35 s) among different locomotion modes. It achieves exceptional agility, including high-speed rolling (818 mm/s, 26 body lengths per second), omnidirectional crawling, jumping, and swimming. Notably, the robot can fold to reduce its occupied volume by 79%, enabling it to traverse confined spaces. We further validate its navigation capabilities in unstructured environments, including discrete obstacles, viscoelastic gelatin surfaces, viscous fluids, 3D-printed gastric surfaces, and a porcine gastric environment. This system offers a versatile strategy for developing high-mobility soft robots for future biomedical applications. The authors present a small-scale, foldable soft electromagnetic robot that features nine locomotion modes and a high rolling speed, enabling navigation through confined and unstructured environments for potential biomedical applications.

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Publication Details

Journal
Nature Communications
Published
2026-09-21
DOI
https://doi.org/10.1038/s41467-026-78006-w
Primary Topic
Micro and Nano Robotics
Type
article
Field-Weighted Citation Impact
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article

A foldable small-scale soft electromagnetic robot for multimodal navigation in confined and unstructured environments

Guoyong Mao, Xingyue Liu, Xiaoyu Song, Yide Liu et al.
Nature Communications
Micro and Nano Robotics
article

A foldable small-scale soft electromagnetic robot for multimodal navigation in confined and unstructured environments

Guoyong Mao, Xingyue Liu, Xiaoyu Song, Yide Liu, Shaoxing Qu, Xiaoyong Zhang, Zhihao Lv, Mengfan Zhang
article en

Abstract

Multimodal locomotion is crucial for an animal’s adaptability in unstructured wild environments. Analogously, in the human gastrointestinal tract, characterized by viscoelastic mucus, complex rugae, and narrow openings like the cardia, multimodal locomotion is also essential for a small-scale soft robot to conduct tasks. Here, we introduce a small-scale, compact, foldable, and robust soft electromagnetic robot with more than nine locomotion modes designed for such a scenario. Featuring a six-spoke elastomer body embedded with liquid metal channels and driven by Laplace forces under a static magnetic field, the robot is capable of rapid transitions ( < 0.35 s) among different locomotion modes. It achieves exceptional agility, including high-speed rolling (818 mm/s, 26 body lengths per second), omnidirectional crawling, jumping, and swimming. Notably, the robot can fold to reduce its occupied volume by 79%, enabling it to traverse confined spaces. We further validate its navigation capabilities in unstructured environments, including discrete obstacles, viscoelastic gelatin surfaces, viscous fluids, 3D-printed gastric surfaces, and a porcine gastric environment. This system offers a versatile strategy for developing high-mobility soft robots for future biomedical applications. The authors present a small-scale, foldable soft electromagnetic robot that features nine locomotion modes and a high rolling speed, enabling navigation through confined and unstructured environments for potential biomedical applications.

Nature Communications
Zhejiang University (CN)
Openalex Percentile: Top 28%
Micro and Nano Robotics
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A foldable small-scale soft electromagnetic robot for multimodal navigation in confined and unstructured environments — Guoyong Mao, Xingyue Liu, et al. · Nature Communications (2026) | TGRS Research Map | TGRS