Autonomous Landing Scheme of VTOL UAV on Moving Ship Using Deep Learning Technique Embedded in Companion Computer

We propose an autonomous landing scheme for Vertical Take-off and Landing Unmanned Aerial Vehicle (VTOL UAV) on a moving ship at sea and this scheme is embedded in a hardware platform - Companion Computer. This mission requires determining the ship’s location, speed, and trajectory, which are significant challenges in the marine environment. This research applies a non-contact method, it is combined deep-learning and visual servoing techniques for real-time measuring of the parameters just mentioned above and tightly coupling with modern navigation logic to ensure the UAV follows a fast and optimal landing trajectory. No prior information about a moving ship’s location and landing pad is needed during the entire VTOL UAV’s landing process. The method aims to improve the performance of the landing. The proposed technique has been evaluated in a hardware in the loop simulation system using Jetson Nano and X-Plane.