logo
ResearchBunny Logo
Multimodal locomotion ultra-thin soft robots for exploration of narrow spaces

Engineering and Technology

Multimodal locomotion ultra-thin soft robots for exploration of narrow spaces

X. Wang, S. Li, et al.

Introducing Thin Soft Robots (TS-Robots), just 1.7 mm thick, these incredible machines can traverse narrow spaces and adapt to various environments, including solid, liquid, and aerial domains. With their unique actuation and high performance, they exhibit impressive locomotion capabilities, crawling, climbing, and swimming with ease. This groundbreaking research was conducted by Xi Wang, Siqian Li, Jung-Che Chang, Jing Liu, Dragos Axinte, and Xin Dong.

00:00
00:00
Playback language: English
Abstract
This paper introduces Thin Soft Robots (TS-Robots), 1.7 mm thick, capable of multimodal locomotion in narrow spaces and across multiple domains (solid, liquid, aerial). These robots utilize a dual-actuation sandwich structure with a tuneable Poisson's ratio tensioning mechanism driven by dielectric elastomers. They demonstrate linear and undulating gaits, high output force (~41 times their weight), and speed (1.16 body length/s and 13.06 body thickness/s). The TS-Robots are shown crawling, climbing, swimming, and collaborating for domain transitions in confined environments.
Publisher
Nature Communications
Published On
Jul 26, 2024
Authors
Xi Wang, Siqian Li, Jung-Che Chang, Jing Liu, Dragos Axinte, Xin Dong
Tags
Thin Soft Robots
multimodal locomotion
dual-actuation
dielectric elastomers
domain transitions
automated systems
soft robotics

Related Publications

Explore these studies to deepen your understanding of the subject.

Computational design of ultra-robust strain sensors for soft robot perception and autonomy
Engineering and Technology

Computational design of ultra-robust strain sensors for soft robot perception and autonomy

H. Yang, S. Ding, et al.

Electrodeposition of ternary compounds for novel PV application and optimisation of electrodeposited CdMnTe thin-films
Engineering and Technology

Electrodeposition of ternary compounds for novel PV application and optimisation of electrodeposited CdMnTe thin-films

A. E. Alam, O. I. Olusola, et al.

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease
Medicine and Health

A multimodal deep learning approach for the prediction of cognitive decline and its effectiveness in clinical trials for Alzheimer’s disease

C. Wang, H. Tachimori, et al.

Control of zeolite framework flexibility for ultra-selective carbon dioxide separation
Engineering and Technology

Control of zeolite framework flexibility for ultra-selective carbon dioxide separation

P. Du, Y. Zhang, et al.

Listen, Learn & Level Up
Over 10,000 hours of research content in 25+ fields, available in 12+ languages.
No more digging through PDFs, just hit play and absorb the world's latest research in your language, on your time.
listen to research audio papers with researchbunny