Pose Adjustment Considering Linear Cross-Section Continuity of Line-Structured Light-Based 3D Tunnel Measurements

In this paper, we propose a method to reduce the position estimation error of line-structured light-based 3D measurements using two unmanned aerial vehicles (UAVs). In addition to the camera used for cross-section measurements, the proposed method uses a camera for pose estimation. The pose of the two cameras can be estimated by performing a 2D-3D registration using an additional camera. Therefore, by alternatively moving both cameras, it is possible to perform 3D measurements of long sections in tunnels. In this method, the measurement procedure is divided into multiple measurement cycles. This process results in two errors. First, as the UAV cannot halt completely in the environment, a drift in the crosssection positions occurs. Second, the rotation of the integrated point cloud of each cycle is inaccurate owing to the pose estimation inaccuracy of the cross-section. To solve the first error, we stabilized the ray vectors using landmarks in the environment. To solve the second error, we compensated for the point cloud rotation based on the fact that the cross-section moves in a straight line at the joints of each measurement area. In the experiments, we performed 3D measurements of a model tunnel with no curvature. The proposed method suppressed the cross-section point cloud drift. In addition, we could calculate the position of the tunnel cross-section with an error of 212 mm in the axial direction, where the error was the largest, over a distance of 30 m.