Description

Maintaining, renovation and construction of railway projects require accurate and up-to-date maps of the current rail situation. Obtaining these maps currently is an expensive and time consuming endeavour.

Therefore, a joint project between our research group Ambient Intelligence and Strukton Rail was conceived to automate the process of mapping. To do so, a dedicated measurement train is used which is equipped with a LiDAR. This LiDAR accurately captures the rail environment as a point cloud. Using deep learning a model was trained to detect objects within the point cloud.

As a result, digitalisation of large segments of rail can be done in a short amount of time.

Video

This video shows the results from the PointPillar object detection model. For this proof-of-concept, the following object classes are detected: masts, signals, tension rods, and relay cabinets. The PointPillar implementation from the MMDetection3D framework was used.

References

1. [Dataset] B. Ton, and Strukton Rail. Annotated Mobile Laser Scans of the Dutch Railway Environment, 4TU.ResearchData, 2024
2. B. Ton and R. Akster, Large Scale Asset Detection Within Railway Scene Point Cloud Data From Mobile Laser Scanning in IEEE Access, vol. 13, pp. 129114-129126, 2025