A Vision and GPS Based System for Autonomous Precision Vertical Landing of UAV Quadcopter

Abstract This research aims to develop an algorithm for the precision vertical landing process on a quadcopter using GPS sensors and computer vision. consists of 2 main parts: GPS-based control used by return home area vision-based in form ArUco marker detection, which is order land precisely. Detection that goes through stages: application threshold ratio calculating black white area, can then be searched four corners marker. The designed works well Webots simulation program with mid-computer specifications. detection fast reliable, so it does not overload processor unit run well. From 30 tests different initial positions, average error position at coordinate X 0.02 meters, coordinates Y 0.03 meters. All test results show inside pad without any parts coming out.