Evidence map›Paper›PMID 40218722›Full record

ArticleSensors (Basel, Switzerland)2025

An Experimental Evaluation of Indoor Localization in Autonomous Mobile Robots.

Mina Khoshrangbaf, Vahid Khalilpour Akram, Moharram Challenger, Orhan Dagdeviren

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 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

4 authors.

Mina KhoshrangbafInternational Computer Institute, Ege University, 35100 Bornova, Izmir, Turkey.ORCID 0009-0000-7963-5372
Vahid Khalilpour AkramInternational Computer Institute, Ege University, 35100 Bornova, Izmir, Turkey.ORCID 0000-0002-4082-6419
Moharram ChallengerDepartment of Computer Science, University of Antwerp and Flanders Make, Middelheimlaan, 2020 Antwerpen, Belgium.ORCID 0000-0002-5436-6070
Orhan DagdevirenDepartment of Computer Engineering, Ege University, 35100 Bornova, Izmir, Turkey.ORCID 0000-0001-8789-5086

Funding

Technological Research Council of Turkey (TUBITAK) 123E094
6 · The paper itself

Abstract

High-precision indoor localization and tracking are essential requirements for the safe navigation and task execution of autonomous mobile robots. Despite the growing importance of mobile robots in various areas, achieving precise indoor localization remains challenging due to signal interference, multipath propagation, and complex indoor layouts. In this work, we present the first comprehensive study comparing the accuracy of Bluetooth low energy (BLE), WiFi, and ultra wideband (UWB) technologies for the indoor localization of mobile robots under various circumstances. In the performed experiments, the error margin of the WiFi-based systems reached 608.7 cm, which is not tolerable for most applications. As a commonly used technology in the existing tracking systems, the accuracy of BLE-based systems is at least 44.12% better than that of WiFi-based systems. The error margin of the BLE-based system in tracking static and mobile robots was 191.7 cm and 340.1 cm, respectively. The experiments showed that even with a limited number of UWB anchors, the system provides acceptable accuracy for tracking the mobile robots. Using only four UWB beacons in an environment of about 431 m

Indexed as

Bluetoothindoor trackinglocalizationmobile robotsultra widebandWiFi

Identifiers

PMID40218722
PMCPMC11991048

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.