Evidence map›Paper›PMID 33450174›Full record

ArticleSoft robotics2021

Soft Robots for Ocean Exploration and Offshore Operations: A Perspective.

Simona Aracri, Francesco Giorgio-Serchi, Giuseppe Suaria, Mohammed E Sayed, Markus P Nemitz, Stephen Mahon, Adam A Stokes

Abstract read
In one paragraph

Article in Soft robotics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
  2. Review
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  5. Ecosystem-Centered Robot Design: Toward Ecoresorbable Sustainability Robots (ESRs).Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Toward Autonomous Self-Healing in Soft Robotics: A Review and Perspective for Future Research.Advanced intelligent systems (Weinheim an der Bergstrasse, Germany) · 2025
    Review
  12. Article
  13. Review
  14. Review
  15. Review
  16. Article
  17. Article
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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

7 authors.

Simona AracriScottish Microelectronics Centre, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom.
Francesco Giorgio-SerchiScottish Microelectronics Centre, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom.
Giuseppe SuariaInstitute of Marine Sciences-National Research Council (ISMAR-CNR), La Spezia, Italy.
Mohammed E SayedScottish Microelectronics Centre, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom.
Markus P NemitzDepartment of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts, USA.
Stephen MahonScottish Microelectronics Centre, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom.
Adam A StokesScottish Microelectronics Centre, Institute for Integrated Micro and Nano Systems, School of Engineering, The University of Edinburgh, Edinburgh, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ocean and human activities related to the sea are under increasing pressure due to climate change, widespread pollution, and growth of the offshore energy sector. Data, in under-sampled regions of the ocean and in the offshore patches where the industrial expansion is taking place, are fundamental to manage successfully a sustainable development and to mitigate climate change. Existing technology cannot cope with the vast and harsh environments that need monitoring and sampling the most. The limiting factors are, among others, the spatial scales of the physical domain, the high pressure, and the strong hydrodynamic perturbations, which require vehicles with a combination of persistent autonomy, augmented efficiency, extreme robustness, and advanced control. In light of the most recent developments in soft robotics technologies, we propose that the use of soft robots may aid in addressing the challenges posed by abyssal and wave-dominated environments. Nevertheless, soft robots also allow for fast and low-cost manufacturing, presenting a new potential problem: marine pollution from ubiquitous soft sampling devices. In this study, the technological and scientific gaps are widely discussed, as they represent the driving factors for the development of soft robotics. Offshore industry supports increasing energy demand and the employment of robots on marine assets is growing. Such expansion needs to be sustained by the knowledge of the oceanic environment, where large remote areas are yet to be explored and adequately sampled. We offer our perspective on the development of sustainable soft systems, indicating the characteristics of the existing soft robots that promote underwater maneuverability, locomotion, and sampling. This perspective encourages an interdisciplinary approach to the design of aquatic soft robots and invites a discussion about the industrial and oceanographic needs that call for their application.

Indexed as

RoboticsClimate ChangeHumansOceanographyOceans and SeasTechnologyabyssal explorationevolution of soft robotsocean explorationoceanographyoffshore operationsustainable development

Identifiers

PMID33450174
PMCPMC8713554

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.