Evidence map›Paper›PMID 34395863›Full record

ArticlePeerJ. Computer science2021

Constructing a cohesive pattern for collective navigation based on a swarm of robotics.

Yehia A Soliman, Sarah N Abdulkader, Taha M Mohamed

Abstract read
In one paragraph

Article in PeerJ. Computer science, 2021. 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

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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

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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

3 authors.

Yehia A SolimanFaculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt.
Sarah N AbdulkaderFaculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt.
Taha M MohamedFaculty of Computers and Artificial Intelligence, Helwan University, Cairo, Egypt.ORCID 0000-0002-2752-9663

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Swarm robotics carries out complex tasks beyond the power of simple individual robots. Limited capabilities of sensing and communication by simple mobile robots have been essential inspirations for aggregation tasks. Aggregation is crucial behavior when performing complex tasks in swarm robotics systems. Many difficulties are facing the aggregation algorithm. These difficulties are as such: this algorithm has to work under the restrictions of no information about positions, no central control, and only local information interaction among robots. This paper proposed a new aggregation algorithm. This algorithm combined with the wave algorithm to achieve collective navigation and the recruitment strategy. In this work, the aggregation algorithm consists of two main phases: the searching phase, and the surrounding phase. The execution time of the proposed algorithm was analyzed. The experimental results showed that the aggregation time in the proposed algorithm was significantly reduced by 41% compared to other algorithms in the literature. Moreover, we analyzed our results using a one-way analysis of variance. Also, our results showed that the increasing swarm size significantly improved the performance of the group.

Indexed as

Aggregation algorithmCollective navigationMobile robotsSwarm robotics

Identifiers

PMID34395863
PMCPMC8323727

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.