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在充满液体的受限空间中的软体自适应多模态运动策略。

Soft-bodied adaptive multimodal locomotion strategies in fluid-filled confined spaces.

作者信息

Ren Ziyu, Zhang Rongjing, Soon Ren Hao, Liu Zemin, Hu Wenqi, Onck Patrick R, Sitti Metin

机构信息

Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany.

Institute for Biomedical Engineering, ETH Zürich, 8092 Zürich, Switzerland.

出版信息

Sci Adv. 2021 Jun 30;7(27). doi: 10.1126/sciadv.abh2022. Print 2021 Jun.


DOI:10.1126/sciadv.abh2022
PMID:34193416
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8245043/
Abstract

Soft-bodied locomotion in fluid-filled confined spaces is critical for future wireless medical robots operating inside vessels, tubes, channels, and cavities of the human body, which are filled with stagnant or flowing biological fluids. However, the active soft-bodied locomotion is challenging to achieve when the robot size is comparable with the cross-sectional dimension of these confined spaces. Here, we propose various control and performance enhancement strategies to let the sheet-shaped soft millirobots achieve multimodal locomotion, including rolling, undulatory crawling, undulatory swimming, and helical surface crawling depending on different fluid-filled confined environments. With these locomotion modes, the sheet-shaped soft robot can navigate through straight or bent gaps with varying sizes, tortuous channels, and tubes with a flowing fluid inside. Such soft robot design along with its control and performance enhancement strategies are promising to be applied in future wireless soft medical robots inside various fluid-filled tight regions of the human body.

摘要

对于未来在充满停滞或流动生物流体的人体血管、管道、通道和腔体内运行的无线医疗机器人而言,在充满流体的受限空间内进行软体运动至关重要。然而,当机器人尺寸与这些受限空间的横截面尺寸相当时,实现主动软体运动具有挑战性。在此,我们提出了各种控制和性能增强策略,以使片状软体微型机器人根据不同的充满流体的受限环境实现多模态运动,包括滚动、波动爬行、波动游泳和螺旋表面爬行。通过这些运动模式,片状软体机器人可以在大小各异的直形或弯曲间隙、曲折通道以及内部有流动流体的管道中导航。这种软体机器人设计及其控制和性能增强策略有望应用于未来在人体各种充满流体的紧密区域内运行的无线软体医疗机器人。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/d769e8593235/abh2022-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/68703da2bb7d/abh2022-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/8dc8c86ae5be/abh2022-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/b27c1b4deafd/abh2022-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/36f2799a238f/abh2022-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/9a6e4bf2d499/abh2022-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/23f42701860e/abh2022-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/d769e8593235/abh2022-f7.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/68703da2bb7d/abh2022-f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/8dc8c86ae5be/abh2022-f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/b27c1b4deafd/abh2022-f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/36f2799a238f/abh2022-f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/9a6e4bf2d499/abh2022-f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/23f42701860e/abh2022-f6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2e0/8245043/d769e8593235/abh2022-f7.jpg

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本文引用的文献

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Sci Adv. 2020-11-6

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