Autonomous Landing For Quadcopter Based On Visual Navigation Modifying Global Positioning System

Abstract

This thesis is to develop a method based on computer vision modifying global positioning system and the drone lands accurately on the ArUco pattern The algorithm of the autonomous landing used for quadcopter is divided into two parts which contains computer vision and aviation formulary: computer vision deal with project correspondences from image coordinate to camera coordinate by using intrinsic matrix Then using EPnP method to convert two-dimension projection points of the image coordinate system into three-dimension reference points of the world coordinate system After obtaining the three-dimensional position and pose estimation of the camera the relative distance between target and camera can be also obtained In aviation formulary the latitude and longitude error can be calculated by the relative distance New latitude and longitude can be obtained by adding and subtracting the original and error Finally the drone can follow the new latitude and longitude and land automatically The quadcopter mounted processor and camera experimented in simple and complex environment waypoint automatic landing and full automatic landing: In the simple environment the experimental data of the height landing error latitude and longitude of the two size ArUco patterns are analyzed separately and the results are discussed The factor of different sizes affects the recognition distance and affects the landing error depending on the duration of action time when the pattern is continuously recognized at low height In the complex environment there are two same size different ID ArUco patterns and complex patterns The visual landslide of the safety detection of various patterns is measured and the changes of the latitude longitude and landing error are analyzed In waypoint automatic landing integrating waypoint planning and automatic landing experimenting in actual flight and discussing the changes in different latitude and longitude curves during flight In the automatic landing adding a small size ArUco pattern allows the drone to continuously correct the GPS before successfully landing without using LAND mode and explore the optimization of the landing error

Date of Award	2019
Original language	English
Supervisor	Wei-Hsiang Lai (Supervisor)