AUTOMATED DETECTION AND CLOSING OF HOLES IN AERIAL POINT CLOUDS USING AN UAS

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

Scaling the world of monocular SLAM with INS-measurements for UAS navigation

The usage of a global positioning system (GPS) corrected inertial navigation system (INS) seems to be advantageous to camera-based pose estimation algorithms for outdoor navigation. The GPS signals lead to a geographical location with an accuracy of a few meters or even up to some centimeters in a setup utilizing correction data. Performing the pose estimation with a camera system has several disadvantages. The high amount of data has to be processed and the robustness may vary because of different environment and weather conditions. Nevertheless, cameras are the most used sensors for various tasks with unmanned aerial systems (UAS) because of their low cost and weight. The research results for vision-based simultaneous localization and mapping (SLAM) algorithms show the great capabilities of vision-based navigation. Therefore, the possibilities of cameras should be investigated for outdoor navigation in conjunction with an INS or as standalone backup solution in the case of an INS failure

Right Atrial Myocardial Remodeling in Children With Atrial Septal Defect Involves Inflammation, Growth, Fibrosis, and Apoptosis.

Introduction: Myocardial remodeling due to large atrial septum defect (ASD) is macroscopically characterized by dilation of the right-sided cardiac cavities secondary to volume overload, the cellular mechanisms of which are not yet understood. We postulated that inflammation, fibrosis, and cell death are actors of right atrial remodeling secondary to ASD. Patients and Methods: In 12 children with large ASD (median age: 63 months), expression of genes coding for proteins involved in the response to cell stress and -protection, inflammation, growth and angiogenesis, fibrosis, and apoptosis was assessed by RT-PCR in right atrial myocardial biopsies taken during cardiac surgery. The presence of cytokines in myocardial cells was confirmed by immunohistochemistry and effective apoptosis by TUNEL assay. Results: In all patients investigated, a cellular response to early mechanical stress with the initiation of early protective mechanisms, of inflammation (and its control), -growth, and -angiogenesis, of fibrosis and apoptosis was present. The apoptotic index assessed by TUNEL assay averaged 0.3%. Conclusions: In children with large ASD, macroscopic right atrial remodeling relates to cellular mechanisms involving the expression of numerous genes that either still act to protect cells and tissues but that also harm as they initiate and/or sustain inflammation, fibrosis, and cell death by apoptosis. This may contribute to long term morbidity in patients with ASD