UAV net landing system for marine operations
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This thesis presents an automatic landing system designed for a fixed-wing unmanned aerialvehicle (UAV) to land in a net placed on ta ship. The UAV used is a Skywalker X8, a cheapand durable airframe, with a Pixhawk as a low-level autopilot while the high-level autopilot iswritten with the LSTS toolchain developed at The Underwater Systems and Technology Laboratoryin Portugal. The high-level autopilot calculates desired speed and attitude with decoupledlateral and longitudinal line-of-sight (LOS) guidance controllers, while the low-level autopilotcalculates desired elevon angles and throttle based on the desired attitude and speed from thehigh-level controller.The main objective was to design and develop a way of predicting the ship motion in seawayensure successful landing attempts. Analysis of ship motion in seaway was conducted whichresulted in that a version of artificial neural networks called long short-term memory networks(LSTM) was used to predict the separate motions of the ship. Software-in-the-loop (SITL)demonstrated successful performance of the automatic landing system and the LSTM showedgood results when predicting the ship motion.