3D Modeling Laser Scanning Lidar Research Surveying Technology

Railway Obstacle Detection Lidar System

figure of railway obstacle detection

In response to the growing demand for railway obstacle detection and monitoring, lidar technology has emerged as an up-and-coming solution.

From a paper by Zongliang Nan et al.

In this study, we developed a mechanical 3D lidar system and meticulously calibrated the point cloud transformation to monitor specific areas precisely.

Based on this foundation, we have devised a novel set of algorithms for obstacle detection within point clouds. These algorithms encompass three key steps: (a) the segmentation of ground point clouds and extraction of track point clouds using our RS-Lo-RANSAC (region select Lo-RANSAC) algorithm; (b) the registration of the BP (background point cloud) and FP (foreground point cloud) via an improved Robust ICP algorithm; and (c) obstacle recognition based on the VFOR (voxel-based feature obstacle recognition) algorithm from the fused point clouds.

This set of algorithms has demonstrated robustness and operational efficiency in our experiments on a dataset obtained from an experimental field. Notably, it enables monitoring obstacles with dimensions of 15 cm × 15 cm × 15 cm. Overall, our study showcases the immense potential of lidar technology in railway obstacle monitoring, presenting a promising solution to enhance safety in this field.


Most research on railway obstacle intrusion focuses on visual detection [4]. However, current optical systems face several challenges, including susceptibility to lighting conditions; reduced obstacle recognition in harsh environments such as rain, snow, and fog; and difficulty in accurately identifying the distance information of obstacles [5].

Staniša et al. [6] proposed a machine learning-based strategy for obstacle detection in cases of pixel-level differences to overcome the low-pixel resolution of the camera system under adverse environmental conditions. Meanwhile, Anand et al. [7] introduced a visual enhancement system that combines infrared cameras and other devices to improve its detection rate in adverse weather conditions.

Lidar is an active sensor. It emits laser pulses towards an object and calculates the distance by collecting and analyzing the echo signals reflected from the object. In recent years, lidar sensors have been widely used in obstacle detection because they are immune to environmental light, have a quick response time, and effectively detect distant obstacles [8,9]. The mainstream 3D lidar used in obstacle measurement includes MEMS (Micro-electro Mechanical System) lidar and traditional mechanical lidar.

For the complete paper CLICK HERE.

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