This method is effective for railway safety and infrastructure change detection. proposed a new method to mix visual and point cloud information, using a hybrid of the Felix robot’s multi-view camera and linear laser. It is of great significance to the healthy development of the intelligent railway system.įor complex scenes such as railways, relevant research institutes at home and abroad have developed various types of orbital mobile laser scanning systems. This paper applies a multi-sensor integrated mobile detection system to railway detection. Combined with the railway experimental track data, the maximum difference in the east and north coordinate direction can be controlled within 7 cm, and the average elevation error is 2.39 cm. This paper corrects the odometer data by identifying railway feature points through deep learning and uses Rauch–Tung–Striebel (RTS) filtering to optimize the trajectory results. Therefore, a point cloud reconstruction method is proposed based on trajectory filtering for a mobile laser scanning system. However, integrating inertial navigation data and mobile laser scanning data to obtain real 3D information about railways has always been an urgent problem to be solved. Mobile laser scanning has the advantages of high efficiency, high precision and automation. Mobile laser scanning is a mobile mapping system based mainly on a laser scanner, inertial measurement unit (IMU) and panoramic camera. Manual measurement cannot meet the requirements of dynamic continuous high-precision holographic measurement during railway outages. This method has high precision, but the amount of data is small, and the measurement efficiency is low.
The traditional railway survey adopts a manual observation method, such as a total station measuring system.
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