Unmanned Aerial Vehicle Landing on Maritime Vessels using Signal Prediction of the Ship Motion

Unmanned aerial vehicles (UAVs) are becoming more prevalent in maritime operations. For safe operation, one of the key challenges of using UAVs at sea is the relative motion that exists between the UAV and ship. For perpetual maritime operations, UAV systems need to be able to land safely on ocean vessels. Determining a 'quiescent period', where the roll and pitch angles of the ship are below a danger threshold, is a challenging problem for UAV systems. In general, current strategies rely on reactive systems and often use sensors on board the maritime vessel. The scope of the current paper is a proof-ofconcept methodology which uses a signal prediction algorithm to facilitate safer autonomous UAV-ship landings. This study uses laser ranging and detecting devices (LIDAR) in conjunction with a signal prediction algorithm (SPA) to forecast when the ship motion is within safe landing limits. ShipMo3D was used to generate twelve trial cases for UAV-ship landings on a 33 m ship. The results show that with the use of the SPA, the number of UAV landing attempts was decreased by an average of 2 attempts, per test case, when compared to a system that did not use an SPA. Moreover, the results indicate that with revised tuning of the SPA, the likelihood of a safe landing can be further improved.