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Enhancing UAV Autonomy and Path Optimization Through SBAS and Visual-Inertial Odometry
Mejora de la autonomía de UAV y optimización de trayectorias mediante odometría visual–inercial integrada con SBAS
DOI:
https://doi.org/10.15446/ing.investig.119122Keywords:
unmanned aerial vehicles (UAVs), visual–inertial odometry (VIO), satellite-based augmentation system (SBAS), factor graph optimization, localization accuracy, GPS-denied navigation (en)vehículos aéreos no tripulados (UAV), odometría visual-inercial (VIO), sistema de aumentación basado en satélites (SBAS), optimización mediante grafo de factores, precisión de localización, navegación en entornos sin GPS (es)
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Unmanned Aerial Vehicles (UAVs) have become indispensable in fields such as disaster response, precision agriculture, environmental monitoring, and surveillance. Their ability to navigate complex and dynamic environments makes them essential for autonomous operations. However, ensuring accurate and reliable state estimation remains a significant challenge, particularly in GPS-denied environments, where traditional navigation systems suffer from drift, localization errors, and trajectory inconsistencies. Addressing these limitations is crucial for improving UAV autonomy and operational efficiency. This study aims to enhance UAV autonomy and trajectory optimization by integrating a Satellite-Based Augmentation System (SBAS) with monocular visual-inertial odometry (VIO) within a factor graph optimization framework. The proposed methodology fuses visual and inertial sensor data, incorporating state constraints and prior knowledge to improve localization accuracy, reduce drift, and manage uncertainty. Experimental evaluations were conducted under different path optimization conditions to assess system performance. Results show that Path 1 achieved the highest optimization score of 0.481, Path 2 showed moderate optimization at 0.130, while Paths 3, 4, and 5 exhibited minimal improvements, with scores of −6.176, −0.041, and −0.113, respectively. These findings confirm the effectiveness of the proposed approach in optimizing UAV trajectories and enhancing real-time navigation accuracy. The study concludes that integrating SBAS with VIO significantly enhances UAV state estimation, offering a promising solution for autonomous aerial operations in both indoor and outdoor environments. This approach provides a robust and scalable framework for improving UAV navigation in critical applications, ensuring greater reliability under GPS-denied conditions.
Los vehículos aéreos no tripulados (UAV) se han vuelto indispensables en campos como la respuesta a desastres, la agricultura de precisión, la monitorización ambiental y la vigilancia. Su capacidad para navegar en entornos complejos y dinámicos los hace esenciales para las operaciones autónomas. Sin embargo, garantizar una estimación de estado precisa y fiable sigue siendo un reto importante, especialmente en entornos sin GPS, donde los sistemas de navegación tradicionales sufren desviaciones, errores de localización e inconsistencias de trayectoria. Abordar estas limitaciones es crucial para mejorar la autonomía y la eficiencia operativa de los UAV. Este estudio tiene como objetivo mejorar la autonomía de los UAV y la optimización de trayectorias mediante la integración de un Sistema de Aumentación Basado en Satélites (SBAS) con odometría visual-inercial monocular (VIO) dentro de un marco de optimización de grafos de factores. La metodología propuesta fusiona datos de sensores visuales e inerciales, incorporando restricciones de estado y conocimiento previo para mejorar la precisión de la localización, reducir las desviaciones y gestionar la incertidumbre. Se realizaron evaluaciones experimentales bajo diferentes condiciones de optimización de trayectorias para evaluar el rendimiento del sistema. Los resultados indican que la Ruta 1 logró la puntuación de optimización más alta, con 0,481; la Ruta 2 mostró una optimización moderada con 0,130; mientras que las Rutas 3, 4 y 5 exhibieron mejoras mínimas, con valores de −6,176, −0,041 y −0,113, respectivamente. Estos hallazgos confirman la eficacia del enfoque propuesto en la optimización de trayectorias de UAV y la mejora de la precisión de la navegación en tiempo real. El estudio concluye que la integración de SBAS con VIO mejora significativamente la estimación del estado de los UAV, ofreciendo una solución prometedora para operaciones aéreas autónomas en entornos interiores y exteriores. Este enfoque proporciona un marco robusto y escalable para mejorar la navegación de UAV en aplicaciones críticas, garantizando una mayor fiabilidad en condiciones de denegación de GPS.
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Copyright (c) 2026 Vengatesan Arumugam, Vasudevan Alagumalai
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