Development of a Landing Period Indicator and the Use of Signal Prediction to Improve Landing Methodologies of Autonomous Unmanned Aerial Vehicles on Maritime Vessels

Abstract

Unmanned aerial vehicles (UAVs) are becoming more prevalent in maritime operations. One of the key challenges to the safe operation of UAVs at sea is the relative motion that exists between the UAV and ship. The scope of this thesis is the creation and evaluation of a methodology for improving the overall landing performance for UAVs using signal prediction and a developed Landing Period Indicator (LPI). The research is conducted in a synthetic environment, where the test vehicle is a quad rotor UAV that is equipped with a Light Detection and Ranging (LIDAR) system to aerially detect ship motion. The observed ship motion is forecasted using signal prediction which identifies and notifies the UAV of potential landing opportunities.The Signal Prediction Algorithm (SPA) is also used for Active Heave Compensation (AHC) to facilitate the UAV in maintaining a safe low hover position above the ship deck. Further, an algorithm is developed to use the AHC system to plan trajectories that land the UAV with a specified impact velocity. The development of the LPI system is presented and its performance as a standalone and supplemental system is evaluated. ShipMo3D was used to generate 105 sets of ship motion in sea states 2-6. The results in this thesis indicate that the developed landing methodologies can improve the landing performance of ocean going helicopters. For the 105 sets of ship motion, using a combination of the SPA, AHC, and the LPI improved landing performance by 25% in two separate test groups. Moreover, the results indicate that with further tuning of the SPA, the likelihood of a safe landing can be further improved.