Evidence map›Paper›PMID 38550252›Full record

ArticleCyborg and bionic systems (Washington, D.C.)2024

Underwater Robots and Key Technologies for Operation Control.

Linxiang Sun, Yu Wang, Xiaolong Hui, Xibo Ma, Xuejian Bai, Min Tan

Abstract read
In one paragraph

Article in Cyborg and bionic systems (Washington, D.C.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
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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

6 authors.

Linxiang SunSchool of Automation, Harbin University of Science and Technology, Harbin, China.ORCID https://orcid.org/0009-0007-3864-8290
Yu WangState Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Xiaolong HuiState Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Xibo MaState Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Xuejian BaiSchool of Electrical Engineering, Liaoning University of Technology, Jinzhou, China.
Min TanInstitute of Automation, Chinese Academy of Sciences, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over time, the utilization of the Underwater Vehicle-Manipulator System (UVMS) has steadily increased in exploring and harnessing marine resources. However, the underwater environment poses big challenges for controlling, navigating, and communicating with UVMS. These challenges have not only spurred the continuous advancement of related technologies, but also made the development of the UVMS even more captivating. This article firstly provides a review of development status of the UVMS and discusses the current limitations and future directions, and then reviews in detail the dynamic and hydrodynamic modeling methods, and analyzes the principles, advantages, and disadvantages of various approaches. Then, we try to review 2 key technologies of operation control methods, including underwater positioning and navigation technologies and vehicle-manipulator coordinated control approaches. Finally, a reasonable prospect for the future development of UVMS is given.

Identifiers

PMID38550252
PMCPMC10976592

What OpenQuestion holds

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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.