Evidence map›Paper›PMID 42187365›Full record

ArticleBiomimetics (Basel, Switzerland)2026

Research on UAV Path Planning Based on Enhanced Artificial Lemming Algorithm.

Yu Liu, Maosheng Fu, Chaochuan Jia, Zhengyu Liu, Xuemei Zhu, Bao Zhou, Jingya Zhang, Hai Liu

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2026. 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

8 authors.

Yu LiuSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.
Maosheng FuSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.
Chaochuan JiaSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.ORCID 0000-0002-0730-3448
Zhengyu LiuSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.
Xuemei ZhuExperimental Training Teaching Management Department, West Anhui University, Lu'an 237012, China.ORCID 0000-0002-8988-1371
Bao ZhouSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.
Jingya ZhangSchool of Electronic Information and Artificial Intelligence, West Anhui University, Lu'an 237012, China.
Hai LiuSchool of Physics and Electronic Engineering, Hubei University of Arts and Science, Xiangyang 441053, China.

Funding

High-level Talent Start-up Project of West Anhui University WGKQ2021052High-level Talent Start-up Project of West Anhui University WGKQ2023003Horizontal Project of West Anhui University 0045022007Horizontal Project of West Anhui University 0045023151Horizontal Project of West Anhui University 0045025141Hubei Provincial Natural Science Foundation - Innovation and Development Joint Fund 2023AFD052Open project of Anhui Dabieshan Academy of Traditional Chinese Medicine TCMADM-2024-07University Innovation Team Project of Department of Education Anhui Province 2023AH010078
6 · The paper itself

Abstract

Unmanned aerial vehicle path planning faces multiple challenges in terms of effectiveness and safety. Traditional optimization methods are difficult to use to effectively find the best route. An enhanced artificial lemming optimization algorithm (ALAEN) is proposed here, which introduces stochastic differential mutation and Beta opposition-based learning into the artificial lemming algorithm (ALA). The comparison with other algorithms on the CEC2017 test set shows that it can effectively improve the optimization ability and convergence speed of the artificial lemming algorithm. Among all algorithms, ALA has an overall ranking of 5.45 and ALAEN has a ranking of 1.34. The ability of ALAEN to solve the actual problem of UAV trajectory planning is tested on two different maps, and it is found that it can effectively improve the path planning ability and ensure safety compared with the ALA. In the small map scene, the average cost function of ALA is 92.999, and the average cost function of ALAEN is 91.598, which is a significant improvement. Compared with other algorithms, ALAEN has the shortest trajectory route and trajectory cost function.

Indexed as

artificial lemming algorithmBetaCOBLpath planningUAV

Identifiers

PMID42187365
PMCPMC13204690

What OpenQuestion holds

Textmetadata
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.