Evidence map›Paper›PMID 36772577›Full record

ArticleSensors (Basel, Switzerland)2023

Line-Features-Based Pose Estimation Method for the Disc Cutter Holder of Shield Machine.

Zhe Xie, Guoli Zhu, Dailin Zhang, Dandan Peng, Jinlong Hu, Yueyu Sun

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Zhe XieSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Guoli ZhuSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Dailin ZhangSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID 0000-0001-9848-4610
Dandan PengSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Jinlong HuSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
Yueyu SunSchool of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.ORCID 0000-0001-5753-6250

Funding

the National Key Research and Development Plan of China 2018YFB1702504
6 · The paper itself

Abstract

To achieve automatic disc cutter replacement of shield machines, measuring the accurate pose of the disc cutter holder by machine vision is crucial. However, under polluted and restricted illumination conditions, achieving pose estimation by vision is a great challenge. This paper proposes a line-features-based pose estimation method for the disc cutter holder of the shield machine by using a monocular camera. For the blurring effect of rounded corners on the image edge, a rounded edge model is established to obtain edge points that better match the 3D model of the workpiece. To obtain the edge search box corresponding to each edge, a contour separation method based on an adaptive threshold region growing method is proposed. By preprocesses on the edge points of each edge, the efficiency and the accuracy of RANSAC linear fitting are improved. The experimental result shows that the proposed pose estimation method is highly reliable and can meet the measurement accuracy requirements in practical engineering applications.

Indexed as

contour extractionline detectionrounded edge modelvisual positioning

Identifiers

PMID36772577
PMCPMC9920199

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.