Algoritmos de enjambre para planificación de rutas en UAV: Una revisión sistemática de características, clasificación y desempeño operativo
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La planificación de rutas para UAV mediante algoritmos de enjambre es clave en la robótica autónoma; sin embargo, faltan revisiones sistemáticas que integren clasificación, características operativas y desempeño. Este estudio propone una taxonomía de cinco categorías, un análisis de frecuencias por dominio y un marco de evaluación con nueve métricas. Siguiendo la metodología PRISMA, se revisaron las bases de datos IEEE Xplore, Scopus, ScienceDirect y ACM Digital Library entre noviembre y diciembre de 2025. De 2761 registros, se incluyeron 31 artículos: 25 estudios primarios y 6 revisiones. Los algoritmos PSO, ACO y ABC concentran el 66 % de las 56 implementaciones identificadas, con especialización en defensa, búsqueda y rescate, y agricultura. Los métodos híbridos constituyen la principal tendencia, mientras que la IA destaca por su potencial de escalabilidad y adaptación. La literatura prioriza la longitud de trayectoria (96 %) y el tiempo de convergencia (88 %), mientras que la eficiencia energética (56 %) y la cobertura de área (48 %) reciben menor atención.
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