Evidence map›Paper›PMID 36991695›Full record

ArticleSensors (Basel, Switzerland)2023

An Online Distance Tracker for Verification of Robotic Systems' Safety.

Esra Guclu, Özlem Örnek, Metin Ozkan, Ahmet Yazici, Zekeriyya Demirci

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

5 authors.

Esra GucluDepartment of Computer Engineering, Eskisehir Osmangazi University, Eskişehir 26480, Turkey.ORCID 0000-0003-1106-5566
Özlem ÖrnekDepartment of Computer Engineering, Eskisehir Osmangazi University, Eskişehir 26480, Turkey.ORCID 0000-0002-8775-8695
Metin OzkanDepartment of Computer Engineering, Eskisehir Osmangazi University, Eskişehir 26480, Turkey.ORCID 0000-0001-7281-3455
Ahmet YaziciDepartment of Computer Engineering, Eskisehir Osmangazi University, Eskişehir 26480, Turkey.ORCID 0000-0001-5589-2032
Zekeriyya DemirciDepartment of Computer Engineering, Eskisehir Osmangazi University, Eskişehir 26480, Turkey.ORCID 0000-0001-9682-4650

Funding

the ECSEL Joint Undertaking (JU) 876852the Scientific and Technical Research Council of Turkey (TUBITAK) 120N800
6 · The paper itself

Abstract

This paper presents an efficient method for minimum distance calculation between a robot and its environment and the implementation framework as a tool for the verification of robotic systems' safety. Collision is the most fundamental safety problem in robotic systems. Therefore, robotic system software must be verified to ensure that there are no risks of collision during development and implementation. The online distance tracker (ODT) is intended to provide minimum distances between the robots and their environments for verification of system software to inspect whether it causes a collision risk. The proposed method employs the representations of the robot and its environment with cylinders and an occupancy map. Furthermore, the bounding box approach improves the performance of the minimum distance calculation regarding computational cost. Finally, the method is applied to a realistically simulated twin of the ROKOS, which is an automated robotic inspection cell for quality control of automotive body-in-white and is actively used in the bus manufacturing industry. The simulation results demonstrate the feasibility and effectiveness of the proposed method.

Indexed as

minimum distance calculationoctree-based maprobotic systemssafety verification

Identifiers

PMID36991695
PMCPMC10057077

What OpenQuestion holds

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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.