Evidence map›Paper›PMID 36504496›Full record

ReviewFrontiers in robotics and AI2022

Optimization and fabrication of programmable domains for soft magnetic robots: A review.

Alistair Bacchetti, Peter Lloyd, Silvia Taccola, Evan Fakhoury, Sandy Cochran, Russell A Harris, Pietro Valdastri, James H Chandler

Abstract readReview
In one paragraph

Review in Frontiers in robotics and AI, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

8 authors.

Alistair BacchettiCentre for Medical and Industrial Ultrasonics, James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom.
Peter LloydScience and Technologies of Robotics in Medicine Laboratory, School of Electronic and Electrical Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, United Kingdom.
Silvia TaccolaFuture Manufacturing Processes Research Group, University of Leeds, Leeds, United Kingdom.
Evan FakhouryIndustrial and Mechanical Engineering Department, Lebanese American University, Byblos, Lebanon.
Sandy CochranCentre for Medical and Industrial Ultrasonics, James Watt School of Engineering, University of Glasgow, Glasgow, United Kingdom.
Russell A HarrisFuture Manufacturing Processes Research Group, University of Leeds, Leeds, United Kingdom.
Pietro ValdastriScience and Technologies of Robotics in Medicine Laboratory, School of Electronic and Electrical Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, United Kingdom.
James H ChandlerScience and Technologies of Robotics in Medicine Laboratory, School of Electronic and Electrical Engineering, Faculty of Engineering and Physical Sciences, University of Leeds, Leeds, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Driven by the aim of realizing functional robotic systems at the milli- and submillimetre scale for biomedical applications, the area of magnetically driven soft devices has received significant recent attention. This has resulted in a new generation of magnetically controlled soft robots with patterns of embedded, programmable domains throughout their structures. This type of programmable magnetic profiling equips magnetic soft robots with shape programmable memory and can be achieved through the distribution of discrete domains (voxels) with variable magnetic densities and magnetization directions. This approach has produced highly compliant, and often bio-inspired structures that are well suited to biomedical applications at small scales, including microfluidic transport and shape-forming surgical catheters. However, to unlock the full potential of magnetic soft robots with improved designs and control, significant challenges remain in their compositional optimization and fabrication. This review considers recent advances and challenges in the interlinked optimization and fabrication aspects of programmable domains within magnetic soft robots. Through a combination of improvements in the computational capacity of novel optimization methods with advances in the resolution, material selection and automation of existing and novel fabrication methods, significant further developments in programmable magnetic soft robots may be realized.

Indexed as

advanced fabricationbio-inspired (BI)design optimizationmagnetic materialsmagnetic soft robotsprogrammable magnetic profilingsoft robots material and design

Identifiers

PMID36504496
PMCPMC9729867

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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.