Evidence map›Paper›PMID 35958683›Full record

ArticleFrontiers in neurorobotics2022

UWB indoor positioning optimization algorithm based on genetic annealing and clustering analysis.

Hua Guo, Mengqi Li, Xuejing Zhang, Xiaotian Gao, Qian Liu

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PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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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.

Hua GuoCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.
Mengqi LiCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.
Xuejing ZhangCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.
Xiaotian GaoCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.
Qian LiuCollege of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Indoor location information is an indispensable parameter for modern intelligent warehouse management and robot navigation. Indoor wireless positioning exhibits large errors due to factors such as indoor non-line-of-sight (NLOS) obstructions. In the present study, the error value under the time of arrival (TOA) algorithm was evaluated, and the trilateral positioning method was optimized to minimize the errors. An optimization algorithm for indoor ultra-wideband (UWB) positioning was designed, which was referred as annealing evolution and clustering fusion optimization algorithm. The algorithm exploited the good local search capability of the simulated annealing algorithm and the good global search capability of the genetic algorithm to optimize cluster analysis. The optimal result from sampled data was quickly determined to achieve effective and accurate positioning. These features reduced the non-direct aiming error in the indoor UWB environment. The final experimental results showed that the optimized algorithm significantly reduced noise interference as well as improved positioning accuracy in an NLOS indoor environment with less than 10 cm positioning error.

Indexed as

annealing evolution algorithmfuzzy c-meanspositioningtriangulation methodUWB

Identifiers

PMID35958683
PMCPMC9360920

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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.