Evidence map›Paper›PMID 39727780›Full record

ArticleBiomimetics (Basel, Switzerland)2024

A Worm-like Soft Robot Based on Adhesion-Controlled Electrohydraulic Actuators.

Yangzhuo Wu, Zhe Sun, Yu Xiang, Jieliang Zhao

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yangzhuo WuSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Zhe SunBeijing Institute of Astronautical Systems Engineering, Beijing 100076, China.
Yu XiangSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.
Jieliang ZhaoSchool of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China.

Funding

Beijing Nova Program 20230484377BIT Teli Young Fellow Recruitment Program RCPT-20220005National Key R&D Program of China 2021YFB3400200National Natural Science Foundation of China 52075038National Natural Science Foundation of China 52375282National Science and Technology Major Project of China SKS-2022031
6 · The paper itself

Abstract

Worms are organisms characterized by simple structures, low energy consumption, and stable movement. Inspired by these characteristics, worm-like soft robots demonstrate exceptional adaptability to unstructured environments, attracting considerable interest in the field of biomimetic engineering. The primary challenge currently involves improving the motion performance of worm-like robots from the perspectives of actuation and anchoring. In this study, a single segment worm-like soft robot driven by electrohydraulic actuators is proposed. The robot consists of a soft actuation module and two symmetrical anchoring modules. The actuation modules enable multi-degree-of-freedom motion of the robot using symmetric dual-electrode electrohydraulic actuators, while the anchoring modules provide active friction control through bistable electrohydraulic actuators. A hierarchical microstructure design is used for the biomimetic adhesive surface, enabling rapid, reversible, and stable attachment to and detachment from different surfaces, thereby improving the robot's surface anchoring performance. Experimental results show that the designed robot can perform peristaltic and bending motions similar to a worm. It achieves rapid bidirectional propulsion on both dry and wet surfaces, with a maximum speed of 10.36 mm/s (over 6 velocity/length ratio (min

Indexed as

biomimetic wet adhesiveelectrohydraulic forcesoft robotworm-inspired

Identifiers

PMID39727780
PMCPMC11727201

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.