The invention discloses an unmanned aerial vehicle
surface reconstruction method based on
point cloud semantic communication, and belongs to the technical field of
point cloud semantic communication. According to the method, the problem that in the
surface reconstruction process of the unmanned aerial vehicle, due to the defects of limited
flight time and computing resources of the unmanned aerial vehicle,
information needs to be completely transmitted in a
transmission bandwidth limited scene, so that
surface reconstruction is smoothly carried out is solved. The invention provides a new semantic communication
algorithm based on the
point cloud, an auto-
encoder architecture with category importance permission is introduced for selective transmission, and unnecessary
data transmission is reduced, so that the bandwidth is saved, and information more related to a surface reconstruction task is transmitted. Secondly, an end-to-end training
system framework is developed, joint optimization of
deep learning is utilized,
data transmission and surface reconstruction processes are simplified, and the
overall efficiency and reconstruction precision of the
system are improved. Wide
verification and
simulation results prove that the framework can complete surface reconstruction with less point
cloud data transmission quantity, the superiority of the framework in efficiency and performance is verified, and the application of the
system in different data types and scenes is expanded.