2026-05-15T03:37:01Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/116152026-05-14T12:06:58Zcom_10259_8983com_10259_5086com_10259_2604col_10259_8984
Bayona Blanco, Eduardo
843
600
0000-0001-5598-3997
Sierra Garcia, Jesús Enrique
737
600
0000-0001-6088-9954
Santos Peñas, Matilde
56068aee-9766-4cb8-b5b5-92b25cfa3dbc
600
2026-05-13T10:56:41Z
2026-05-13T10:56:41Z
2025-03
0266-4720
https://hdl.handle.net/10259/11615
10.1111/exsy.13836
1468-0394
In the context of industrial automation, optimising automated guided vehicle (AGV) trajectories is crucial for enhancing op-erational efficiency and safety. They must travel in crowded work areas and cross narrow corridors with strict safety and timerequirements. Bio-inspired optimization algorithms have emerged as a promising approach to deal with complex optimiza-tion scenarios. Thus, this paper explores the ability of three novel bio-inspired algorithms: the Bat Algorithm (BA), the WhaleOptimization Algorithm (WOA) and the Gazelle Optimization Algorithm (GOA); to optimise the AGV path planning in complexenvironments. To do it, a new optimization strategy is described: the AGV trajectory is based on clothoid curves and a specialisedpiece-wise fitness function which prioritises safety and efficiency is designed. Simulation experiments were conducted acrossdifferent occupancy maps to evaluate the performance of each algorithm. WOA demonstrates faster optimization providingsuitable safety solutions 4 times faster than GOA. Meanwhile, GOA gives solutions with better safety metrics but demands morecomputational time. The study highlights the potential of bio-inspired approaches for AGV trajectory optimisation and suggestsavenues for future research, including hybrid algorithm development.
Open access funding provided by FEDER European Funds and the Junta De Castilla y León under the Research and Innovation Strategy for Smart Specialization (RIS3) of Castilla y León 2021-2027
eng
Wiley
Expert Systems. 2025, V. 42, n. 3, e13836
https://doi.org/10.1111/exsy.13836
Atribución 4.0 Internacional
http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
AGV
Bio-inspired algorithms
Industry 4.0
Optimization
Computer algorithms
Algoritmos computacionales
Diseño industrial
Industrial design
Improving Safety and Efficiency of Industrial Vehicles by Bio‐Inspired Algorithms
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Expert Systems
42
3
https://ror.org/051jb1k20
Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE)
hybrid-oa
1
2488,66 EUR
9100199480
John Wiley & Sons
2025-04-30
2025-11-14
2025-01-01
2028-12-31
10.1111/exsy.13836
THUMBNAIL
Bayona-es_2025.pdf.jpg
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oai:riubu.ubu.es:10259/11615
2026-05-14 14:06:58.837
Repositorio Institucional de la Universidad de Burgos
bubrep@ubu.es
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