An improved roosters algorithm for constrained 3D UAV path planning in urban environments

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dc.authoridAta, Baris/0000-0003-4773-0564
dc.authoridGençal, Mashar/0000-0002-1317-3950
dc.authoridKilinc, Emre/0000-0002-5250-9322
dc.contributor.authorGencal, Mashar Cenk
dc.contributor.authorAta, Baris
dc.contributor.authorKurucan, Mehmet
dc.contributor.authorKilinc, Emre
dc.date.accessioned2026-02-27T07:33:32Z
dc.date.available2026-02-27T07:33:32Z
dc.date.issued2025
dc.description.abstractUrban environments impose complex challenges for the navigation of unmanned aerial vehicles (UAVs), including dense obstacles, no-fly zones, energy constraints, and regulatory restrictions. Addressing these challenges requires efficient and robust optimization techniques. This study introduces the Improved Roosters Algorithm (IRA), a novel metaheuristic inspired by the natural dominance behavior of roosters, tailored for constrained 3D UAV path planning in urban scenarios. Unlike existing metaheuristics, IRA introduces a spiral dancing operator, adaptive constraint handling, and a hierarchical population structure. These innovations directly target the lack of adaptive mechanisms in constraint-rich urban environments, enabling more reliable and realistic UAV path planning. The performance of IRA is benchmarked against Particle Swarm Optimization (PSO), Standard Genetic Algorithm (SGA), Differential Evolution (DE), Grey Wolf Optimizer (GWO) and the original Roosters Algorithm (RA) across three increasingly complex simulation scenarios. Experimental results demonstrate that IRA consistently outperforms the baseline methods in terms of feasibility and optimality, validating its potential as a competitive tool for UAV mission planning in realistic urban environments.
dc.identifier.doi10.1038/s41598-025-24752-8
dc.identifier.issn2045-2322
dc.identifier.issue1
dc.identifier.pmid41266587
dc.identifier.urihttp://dx.doi.org/10.1038/s41598-025-24752-8
dc.identifier.urihttps://hdl.handle.net/20.500.14669/4630
dc.identifier.volume15
dc.identifier.wosWOS:001620594700024
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherNature Portfolio
dc.relation.ispartofScientific Reports
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20260302
dc.subjectMetaheuristic algorithms
dc.subjectMulti-objective optimization
dc.subjectPath planning
dc.subjectUnmanned aerial vehicles
dc.titleAn improved roosters algorithm for constrained 3D UAV path planning in urban environments
dc.typeArticle

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