Unmanned Aerial Vehicle (UAV) autonomous returning and navigation planning

Abstract

The purpose of this study was to build a vision-based automatic landing system for fixed-wing Unmanned Aerial Vehicle (UAV) due to a Global Positioning System (GPS) denied environment to ensure flight safety Through the onboard camera installed on the center of the aircraft belly orthogonal projection images were taken to implement the method of image stitching by SURF algorithm By image stitching a two-dimensional panoramic map was created as a global map; when the flight altitude changed the instant image was assigned as a local map With the two maps a dual-scale image relation was connected to confirm the location of the aircraft in space After completing the built up of the map the process of image recognition could be applied to detect the suitable landing candidates e g runways or straight highway sections by YOLO – a real-time object detecting system With the selected region to land verified the onboard computer could calculate the gliding route according to standard approach procedure and guide the aircraft to the final touch down by real-time images There are four goals to approach in this thesis: (a)The realization of image stitching using orthogonal projection aerial images (b)The recognition between dual-scale images and aircraft locations (c)Integration of the technology about image identification and classification about runways and highways (d)The guidance of the landing target

Date of Award	2020
Original language	English
Supervisor	Chieh-Li Chen (Supervisor)