Automated Detection and Closing of Holes in Aerial Point Clouds Using an Uas

Abstract

ABSTRACT:3D terrain models are an important instrument in areas like geology, agriculture and reconnaissance. Using an automated UAS with a line-based LiDAR can create terrain models fast and easily even from large areas. But the resulting point cloud may contain holes and therefore be incomplete. This might happen due to occlusions, a missed flight route due to wind or simply as a result of changes in the ground height which would alter the swath of the LiDAR system. This paper proposes a method to detect holes in 3D point clouds generated during the flight and adjust the course in order to close them. First, a grid-based search for holes in the horizontal ground plane is performed. Then a check for vertical holes mainly created by buildings walls is done. Due to occlusions and steep LiDAR angles, closing the vertical gaps may be difficult or even impossible. Therefore, the current approach deals with holes in the ground plane and only marks the vertical holes in such a way that the operator can decide on further actions regarding them. The aim is to efficiently create point clouds which can be used for the generation of complete 3D terrain models.

ROV-Based Autonomous Maneuvering for Ship Hull Inspection with Coverage Monitoring

“…In [19], the boundaries are extracted using 2D phase information by detecting phase jumps, and the holes are then repaired with an algorithm based on Structure From Motion (SFM) and point cloud registration. The method by [20] converts first the point cloud into a voxel grid based on the same methods as previously mentioned to detect boundaries. However, to detect height jumps and vertical away holes, thresholding operations are performed.…”

“…Fig 20. The results of another autonomous inspection are displayed with in (a), the 3D voxel map and in (b), the maneuvering errors…”