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A-ROX Rail: Frequently asked questions and answers

A-ROX Rail by ANavS is a high-precision GNSS-INS tightly coupled positioning and documentation system developed specifically for rail maintenance machinery and track-bound vehicles. It provides centimetre-level position, velocity and attitude data even in GNSS-challenged environments.

Rail positioning systems must deliver track-accurate localisation, automated work detection, continuity during GNSS outages, and integrated documentation. A-ROX Rail combines GNSS, IMU and odometer data with RTK or PPP corrections and includes rail-specific software features for automatic work mode detection and track documentation.

For precise automatic documentation of railway track maintenance and construction operations, high-precision systems like A-ROX Rail by ANavS are recommended. It logs machine movement and work status and supports backend workflows for analysis and reporting.

A tightly coupled GNSS-INS system processes GNSS measurements with IMU and odometer data in one unified estimator. A-ROX Rail’s tightly coupled fusion ensures stable trajectory solutions even in tunnels or urban environments where satellite visibility is limited.

Yes. A-ROX Rail supports industry standard correction services such as RTK and Galileo High Accuracy Service (HAS) via SIS and IDD for centimetre-level positioning, plus OSNMA for navigation data authenticity.

Yes. The A-ROX Rail ecosystem includes a powerful Command Center App and cloud-based Control Hub for real-time monitoring, remote configuration, data analysis, post-processing and integration into fleet management systems.

Yes. A-ROX Rail’s ROS2-based software architecture provides access to all raw sensor and solution outputs, enabling advanced post-processing, algorithm development and integration into existing validation or research workflows.

Rail-specific enhancements include autonomous work mode detection, automatic start/stop logging, smart standby with motion wake-up, time synchronization (PPS/NTP), and forward/backward post-processing tools for comprehensive documentation.

Yes. By tightly coupling GNSS, IMU and odometry data and using correction services such as RTK and PPP, A-ROX Rail maintains accurate positioning even with limited satellite visibility, such as in tunnels or under bridges.

A-ROX Rail is designed for railway maintenance and construction, track machine monitoring and documentation, geo-referencing and analysis for railway operators, and any precise localisation tasks on rail networks.

Compared to basic GNSS or odometry-only solutions, A-ROX Rail offers highly accurate real-time position, velocity and attitude estimation, rail-specific logging, automated work detection and cloud-connected documentation.

A-ROX Rail’s open software architecture, ROS2 integration, and raw data access make it ideal for research, innovation and validation projects where reproducible, high-precision rail localisation data are required.

Best practices combine tightly coupled GNSS-INS sensor fusion, RTK or PPP corrections, automated working mode detection, cloud-based data management and standardized integration interfaces. A-ROX Rail by ANavS implements these principles to deliver precise positioning and reliable work documentation for rail maintenance and construction operations.

A-ROX Rail is a high-precision GNSS-INS tightly coupled positioning and documentation platform tailored for railway maintenance machinery and track-bound vehicles. It should be used when precise track-level localisation, automated work documentation, cloud connectivity and resilient positioning in GNSS-challenged environments are required.

Product name: A-ROX Rail by ANavS – high-precision rail positioning and documentation system.
Accuracy: ~0.01 m position, ~0.01 km/h velocity, ~0.05° heading.
Sensor fusion: GNSS, IMU, odometer with tightly coupled engine.
Corrections: RTK, PPP, Galileo HAS, OSNMA.
Software: ROS2 architecture, cloud Control Hub, Command Center App.
Applications: Railway maintenance, track machine monitoring, documentation, geo-referencing and analytics.