Evidence map›Paper›PMID 42521713›Full record

ArticleScientific reports2026

A novel pray optimization algorithm for six degree of freedom robotic arm trajectory planning.

Assem F Alabu-Husain, Mostafa A ElBahloul, Mahmoud M Saafan, Eman M El-Gendy

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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.

Assem F Alabu-HusainMechatronics Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
Mostafa A ElBahloulProduction Engineering and Mechanical Design Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
Mahmoud M SaafanComputers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt.
Eman M El-GendyComputers and Control Systems Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt. eman_elgendy@mans.edu.eg.ORCID https://orcid.org/0000-0001-7468-4087

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study introduces the Pray Optimization Algorithm (POA), a novel metaheuristic inspired by the procedural rituals of Islamic pray, designed to solve complex engineering and robotic manipulator problems. The mathematical model is structured into three distinct phases: Phase I simulates searching for a suitable mosque; Phase II models congregational alignment (lining up for pray); and Phase III implements a cumulative scoring system to drive convergence. The efficacy of the POA is initially validated on the CEC2017 benchmark suite through comparative analysis with six high-performing metaheuristic algorithms. The algorithm's statistical superiority is subsequently confirmed using the Wilcoxon rank-sum and Friedman tests. To verify its practical applicability, the POA is deployed to solve three classical real-world engineering optimization problems. Ultimately, the algorithm demonstrates superior performance when compared against five state-of-the-art methods in optimizing the trajectory planning of a 6-DOF industrial robotic arm. These findings substantiate the effectiveness of the proposed POA in navigating constrained, real-world engineering search spaces.

Indexed as

Benchmark functionsMetaheuristic optimizationPray optimization algorithmRobotic armTrajectory planning

Identifiers

PMID42521713
PMCPMC13415880

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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.