Digital Twin Generation via Robotic SLAM for Wireless Ray-Tracing Applications

Abstract

Wireless digital twins are useful for analyzing radio propagation in real environments. They can be used to study coverage, propagation paths, and channel characteristics before a wireless system is deployed. However, creating an accurate three dimensional scene manually is time-consuming, especially in indoor environments with walls, doors, glass surfaces, corridors, and other structures that influence signal propagation. SLAM can provide a point cloud map of such environments, but this output cannot be directly used for wireless ray tracing. A point cloud only contains discrete points and usually does not include continuous surfaces, clean mesh geometry, or radio material information. This thesis proposes a workflow that converts robotic SLAM data into a wireless digital twin that can be used in Sionna RT. In the proposed workflow, a mobile robot equipped with LiDAR, camera, and IMU sensors is used to collect indoor environmental data. The recorded data are processed by SLAM to reconstruct the main geometry of the environment as a point cloud map. The point cloud is then processed through filtering, surface reconstruction, mesh cleaning, simplification, and material assignment. After these steps, the model is exported as a Sionna RT-compatible scene. In Sionna RT, the transmitter and receiver positions, antenna settings, carrier frequency, and ray-tracing parameters are configured. The simulation is then used to compute propagation paths and channel results, including radio map, PDP, CFR, AoA, and AoD. The results show that the generated digital twin can be used for ray-tracing-based wireless simulation. The simulation outputs also show that mapping quality, mesh completeness, surface roughness, coordinate consistency, and material assignment can influence the channel results. These factors affect path delay, received power, angular information, and frequency response. Overall, this thesis shows that robotic SLAM and Sionna RT can be combined to generate indoor wireless digital twins, and it provides a practical workflow for converting real indoor mapping data into a ray-tracing scene.