This paper presents a novel approach that integrates 5G Time of Arrival (ToA) measurements into ORB-SLAM3 to enable global localization and enhance mapping capabilities for indoor drone navigation. We extend ORB-SLAM3's optimization pipeline to jointly process ToA data from 5G base stations alongside visual and inertial measurements while estimating system biases. This integration transforms the inherently local SLAM estimates into globally referenced trajectories and effectively resolves scale ambiguity in monocular configurations. Our method is evaluated using both Aerolab indoor datasets with RGB-D cameras and the EuRoC MAV benchmark, complemented by simulated 5G ToA measurements at 28 GHz and 78 GHz frequencies using MATLAB and QuaDRiGa. Extensive experiments across multiple SLAM configurations demonstrate that ToA integration enables consistent global positioning across all modes while maintaining local accuracy. For monocular configurations, ToA integration successfully resolves scale ambiguity and improves consistency. We further investigate scenarios with unknown base station positions and demonstrate that ToA measurements can effectively serve as an alternative to loop closure for drift correction. We also analyze how different geometric arrangements of base stations impact SLAM performance. Comparative analysis with state-of-the-art methods, including UWB-VO, confirms our approach's robustness even with lower measurement frequencies and sequential base station operation. The results validate that 5G ToA integration provides substantial benefits for global SLAM applications, particularly in challenging indoor environments where accurate positioning is critical.

翻译：本文提出一种创新方法，将5G到达时间测量值集成至ORB-SLAM3框架中，旨在实现室内无人机导航的全局定位并增强建图能力。我们扩展了ORB-SLAM3的优化流程，使其能够联合处理来自5G基站的ToA数据、视觉与惯性测量值，同时估计系统偏差。该集成将本质上属于局部性质的SLAM估计转换为全局参考轨迹，并有效解决了单目配置中的尺度模糊性问题。我们采用配备RGB-D相机的Aerolab室内数据集与EuRoC MAV基准进行评估，并辅以通过MATLAB和QuaDRiGa在28 GHz与78 GHz频段生成的仿真5G ToA测量数据。在多种SLAM配置下的大量实验表明，ToA集成能够在所有模式下实现一致的全局定位，同时保持局部精度。对于单目配置，ToA集成成功解决了尺度模糊问题并提升了系统一致性。我们进一步研究了基站位置未知的场景，证明ToA测量可有效作为回环检测的替代方案进行漂移校正。同时分析了基站不同几何布局对SLAM性能的影响。与UWB-VO等前沿方法的对比分析证实，即使在较低测量频率和顺序基站操作的条件下，本方法仍具有较强鲁棒性。实验结果验证了5G ToA集成为全局SLAM应用带来的显著优势，尤其在精准定位至关重要的复杂室内环境中。