Investigation of the Influence of External Conditions on the Process of Automated Landing of an UAV on a Seismic Sensor Using Technical Vision

This paper describes a series of experiments in the simulation environment Gazebo aimed at studying the influence of external weather conditions on the automatic landing of an unmanned aerial vehicle (UAV) on a seismic sensor using computer vision and a previously developed control system based on proportional-integral-derivative (PID) and polynomial controllers. As part of the research, methods for modeling external weather conditions were developed and landing experiments were carried out simulating weather conditions such as wind, light, fog, and precipitation, including their combinations. In all experiments, successful landing on the seismic sensor was achieved; during the experiments, landing time and its accuracy were measured. The graphical and statistical analysis of the obtained results revealed the influence of illumination, precipitation and wind on the UAV landing time, and the introduction of wind into the simulation under any other external conditions led to the most significant increase in landing time. At the same time, the study failed to identify a systemic negative influence of external conditions on landing accuracy. 92.4% of pairwise tests for accuracy samples confirmed the hypothesis of no significant differences. The results obtained provide valuable information for further improvement of autonomous automatic landing systems for UAVs without the use of satellite navigation systems.