Evidence map›Paper›PMID 41272069›Full record

ArticleScientific reports2025

The method of reflection-based marker detection and identification to ensure accurate AGV docking.

Piotr Biernacki, Adam Ziebinski

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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

2 authors.

Piotr BiernackiInstitute of Theoretical and Applied Informatics, Polish Academy of Sciences, 44-100, Gliwice, Poland. pbiernacki@iitis.pl.
Adam ZiebinskiDepartment of Distributed Systems and Informatic Devices, Silesian University of Technology, 44-100, Gliwice, Poland.

Funding

Project "Automated Guided Vehicles integrated with Collaborative Robots for Smart Industry Perspective" NOR/POLNOR/CoBotAGV/0027/2019-00
6 · The paper itself

Abstract

Accurate localization is essential for Automated Guided Vehicles (AGVs) to ensure reliable motion planning and precise execution of docking tasks. A key challenge lies in robust environmental perception for industrial applications. This paper introduces a novel reflection-based marker detection and identification method that relies solely on two-dimensional Light Detection and Ranging (2D LiDAR) technology. The proposed docking method and 2D marker design enable the AGV to accurately estimate the marker's distance and orientation, reliably identify it, and determine the docking point. Experimental validation on a heavy industrial AGV demonstrated that the docking method achieves accuracy of up to 1 cm in position and below 0.05 degree in YAW orientation. As a result, the AGV achieved docking precision at an assembly station with a standard deviation below 2 cm in X and Y axes and YAW orientation below 1.8 degree.

Indexed as

2D LiDAR2D markerAGV dockingobject detectionobject identification

Identifiers

PMID41272069
PMCPMC12638854

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.