Modified depth map post-processing method for problems of accident-free UAV driving in urban infrastructure

Abstract

Formulation of the problem. Currently, unmanned aerial vehicles (UAVs) are actively used to solve cross-industry tasks, such as photo and video filming of the surrounding space, remote analysis of surrounding objects, cargo delivery, monitoring the state of transport routes and mining complexes. UAVs are also used in emergency areas where the presence of people is associated with a threat to life. Since good orientation in space is necessary in all of these areas, UAV orientation in urban infrastructure is of great practical importance. For example, for accident-free driving of UAVs, determining the distance to obstacles (image depth maps) and constructing the trajectory of their flight is of great importance, which is relevant for precise UAV orientation in urban infrastructure. Target. Propose a modified method for post-processing the image depth map for the problems of accident-free driving of UAVs in urban infrastructure. Results. Existing methods and algorithms for converting from 2D signals to 3D signals in image analysis and display systems are considered. A study of the method of post-processing of the image depth map was carried out and its modification was proposed. To evaluate the effectiveness of the developed post-processing method, a comparative analysis of depth maps for various test images obtained by the original method and its modification was performed. Root-mean-square errors are obtained for the proposed and original post-processing methods for the considered test images. Practical significance. The presented modified image depth map post-processing method makes it possible to build sharper image depth maps, which provides more accurate UAV orientation in urban infrastructure.