Evidence map›Paper›PMID 36909973›Full record

ArticleComputational intelligence and neuroscience2023

The Path Planning and Location Method of Inspection Robot in a Large Storage Tank Bottom.

Yinchu Wang, Haijiang Zhu, Yue Yu, Bin Hu

Abstract read
In one paragraph

Article in Computational intelligence and neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Yinchu WangCollege of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.ORCID https://orcid.org/0000-0001-6850-3817
Haijiang ZhuCollege of Information Science and Technology, Beijing University of Chemical Technology, Beijing 100029, China.ORCID https://orcid.org/0000-0002-0609-3610
Yue YuChina Special Equipment Inspection and Research Institute, Beijing 100026, China.ORCID https://orcid.org/0009-0008-3174-4252
Bin HuChina Special Equipment Inspection and Research Institute, Beijing 100026, China.ORCID https://orcid.org/0009-0003-8046-7523

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development of robot technology, inspection robots have been applied to the defect detection of large tanks. However, the existing path planning algorithm of the tank bottom detection robot is easy to fall into the local minimum, and the path is not smooth. Besides, the positioning of the tank bottom detection robot is not accurate. This article proposes a path planning and location algorithm for the large tank bottom detection robot. Specifically, we design a preset spiral path according to the shape of the tank bottom, and a rotating potential field (RPF) near the obstacle is added to avoid the problem of path planning falling into a local minimum. We obtained accurate and smooth planning results. Compared with the state-of-the-art, the RPF method reduced the average RMSE by 9.49%. In addition, by measuring the acoustic emission distance, the three-point positioning algorithm can be used to achieve the calculation of the robot position detection in the proposed method, and the average positioning error on the spiral path is only 0.0748 ± 0.0032.

Indexed as

RoboticsAcousticsAlgorithms

Identifiers

PMID36909973
PMCPMC9998163

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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.