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Updated: Feb 19, 2026

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

Mapeo semántico consciente de objetos utilizando funciones de densidad de probabilidad para la relocalización y la

Alicia Mora¹, Alberto Mendez², Luis Moreno²

¹RoboticsLab, Department of Automation and Systems Engineering, Universidad Carlos III de Madrid, Leganes, Madrid, 28911, Spain. almorav@ing.uc3m.es.

Scientific reports

|February 17, 2026

Resumen

Este estudio presenta un marco de mapeo semántico consciente de objetos para robots de interior. Utiliza funciones de densidad de probabilidad (PDF) para crear mapas 3D compactos y robustos, mejorando la navegación y la relocalización en entornos complejos.

Sus antecedentes:

Los robots de interior requieren mapas semánticos escalables para entornos complejos.
Los mapas semánticos existentes son demasiado densos y computacionalmente costosos o carecen de detalle geométrico.
Existe una compensación entre el detalle del mapa y la eficiencia computacional, lo que limita las aplicaciones en el mundo real.

Conclusiones:

El marco de mapeo probabilístico centrado en el objeto ofrece una representación unificada para múltiples comportamientos robóticos.
Este enfoque apoya la comprensión funcional de la escena para la navegación consciente del contexto.
Validado en conjuntos de datos de referencia y entornos de apartamentos del mundo real, mostrando ventajas significativas.

Palabras clave:

Conciencia de objetos Planificación de rutas Funciones de densidad de probabilidad Mapeo semántico Relocalización semántica

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