Evidence map›Paper›PMID 33143242›Full record

ReviewSensors (Basel, Switzerland)2020

Localisation of Unmanned Underwater Vehicles (UUVs) in Complex and Confined Environments: A Review.

Simon Watson, Daniel A Duecker, Keir Groves

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
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

3 authors.

Simon WatsonDepartment of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0001-9783-0147
Daniel A DueckerInstitute of Mechanics and Ocean Engineering, Hamburg University of Technology, 21073 Hamburg, Germany.ORCID 0000-0001-7256-6984
Keir GrovesDepartment of Electrical and Electronic Engineering, The University of Manchester, Manchester M13 9PL, UK.ORCID 0000-0002-0763-7069

Funding

Engineering and Physical Sciences Research Council EP/R026084/1 and EP/P01366X/1
6 · The paper itself

Abstract

The inspection of aquatic environments is a challenging activity, which is made more difficult if the environment is complex or confined, such as those that are found in nuclear storage facilities and accident sites, marinas and boatyards, liquid storage tanks, or flooded tunnels and sewers. Human inspections of these environments are often dangerous or infeasible, so remote inspection using unmanned underwater vehicles (UUVs) is used. Due to access restrictions and environmental limitations, such as low illumination levels, turbidity, and a lack of salient features, traditional localisation systems that have been developed for use in large bodies of water cannot be used. This means that UUV capabilities are severely restricted to manually controlled low-quality visual inspections, generating non-geospatially located data. The localisation of UUVs in these environments would enable the autonomous behaviour and the development of accurate maps. This article presents a review of the state-of-the-art in localisation technologies for these environments and identifies areas of future research to overcome the challenges posed.

Indexed as

complex environmentslocalisationunmanned underwater vehicle (UUV)

Identifiers

PMID33143242
PMCPMC7663020

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.