Evidence map›Paper›PMID 37056427›Full record

ReviewNational science review2023

Climbing robots for manufacturing.

Bo Tao, Zeyu Gong, Han Ding

Abstract readReview
In one paragraph

Review in National science review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Science advances · 2025
    Article
  3. Article
  4. Article
  5. 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.

Bo TaoState Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Zeyu GongState Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Han DingState Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Robotized intelligent manufacturing is a growing trend in the manufacturing of large and complex components in aviation, aerospace, marine engineering and other industries. With their expansive workspaces and flexible deployment, climbing manufacturing robots can create a revolutionary manufacturing paradigm for large and complex components. This paper defines the climbing manufacturing robot based on the application status of climbing robots and then analyzes four key technical requirements: adhesion, locomotion, localization and control. Subsequently, the current research status of climbing robots in these four areas is classified and reviewed, along with a clarification of the research frontiers and trends in each area, and the applicability of the relevant research to manufacturing-oriented climbing robotic systems is analyzed. Finally, by concluding the development trends of robotized intelligent manufacturing equipment in terms of manufacturing dimension and scale, environmental adaptability and cluster collaboration capability, we clarify the major challenges for climbing manufacturing robots in terms of adhesion principles, motion mechanisms, positioning technology and control methods, and propose future research directions in these fields.

Indexed as

climbing manufacturing robotclimbing robotrobotized intelligent manufacturing

Identifiers

PMID37056427
PMCPMC10089588

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.