Testing and Simulating a Simplified Precision Autonomous Landing Algorithm for Unmanned Aerial Vehicles (UAV)

Drones are capable of carrying objects of various types. However, their landing pad detection systems did not consistently perform as intended to environmental conditions, such as inclement weather or inadequate illumination. This article presents a simplified precision landing algorithm for unmanned aerial vehicles (UAV) with the objective of enhancing accuracy of the landing procedure. The proposed system relies on integrating a GPS module, an ultrasonic distance sensor and a proximity sensor. The GPS is responsible for navigating the drone to the designated Target location, the ultrasonic sensor assists in decreasing the drone’s altitude, and the proximity sensor ensures an accurate detection of the landing pad. The UAV is required to execute landings in open environments, where fluctuating environmental conditions and mobile landing pads represent principal challenges. Therefore, the model takes into account has such difficulties as reduced stability, caused by wind or non-permanent placement of the landing pad over time. The study included simulations performed in the Python environment, which allowed to test the algorithm’s effectiveness in different scenarios, such as variable weather conditions and landing pads moving at different speeds. Simulation results show that the simplified model allows to limit the landing error to a few centimeters, which proves its effectiveness during a safe UAV precision landing procedure. Future testing performed by the authors will encompass the development of a dynamic algorithm, physical modifications to the UAV and a comparative of simulation results.