Bulk cargo volume measurement for moving dump trucks with a single-layer LiDAR and a camera

The paper addresses the problem of non–contact bulk cargo volume estimation for moving dump trucks. A common scanning method that lets to evaluate the volume of cargo of complex surface for a moving truck implies two single-layer (2D) Light Detection and Ranging (LiDAR) sensors: one is used to scan a vehicle in a plane perpendicular to its movement and the second – to estimate vehicle displacements and restore scans positions on an axis along vehicle movement direction. While LiDAR sensors provide reliable measurement signals in controlled environments their efficacy drastically decreases under challenging outdoor conditions: sand dust, fog, rain heavy precipitation cause false detections and distort LiDARs signal. Thus, vehicle displacements estimated with a highly corrupted LiDAR signal can not be used for a reliable measurement as they may lead to significant volume calculation errors. Partially this is solved in multi-echo lidar where distorted data could be separated from the relevant. In contrast to the single-echo 2D LiDAR, image data from industrial cameras is less sensitive to sand dust or fog. In the paper we propose a novel bulk cargo estimation method that implies only one 2D LiDAR and for vehicle displacements estimation utilizes a camera and computer vision methods. As we demonstrate on a diverse dataset of 730 pairs of dump truck passes from an operating sand pit, the proposed method is more accurate than the two 2D LiDARs baseline while requiring a significantly cheaper sensor. In case if a camera is already present in the volume measurement system and utilized for loaded material classification then the proposed method lets to reduce the cost of solution by the cost of one lidar.