ABSTRAK DARIEL VALDANO
PUBLIC Alice Diniarti COVER DARIEL VALDANO
PUBLIC Alice Diniarti BAB 1 DARIEL VALDANO
PUBLIC Alice Diniarti BAB 2 DARIEL VALDANO
PUBLIC Alice Diniarti BAB 3 DARIEL VALDANO
PUBLIC Alice Diniarti BAB 4 DARIEL VALDANO
PUBLIC Alice Diniarti BAB 5 DARIEL VALDANO
PUBLIC Alice Diniarti PUSTAKA DARIEL VALDANO
PUBLIC Alice Diniarti
In this thesis, a method to create an Autonomous Landing System for use in Naval-based
UAV is formulated by incorporating a deep-learning computer vision model based on
YOLOv4 combined with a distance estimator to deduce a landing coordinate on a UAV
equipped with a camera and an embedded computer. Images from the camera is processed
using the developed vision model, outputting a bounding box that are then calculated using
stadiametric rangefinding to measure distance. The attitudes of the camera as well as the UAV
is combined with the measured distance, outputting a coordinate that can then be fed to the
UAV????s Flight Controller. During testing, the system starts measuring distance to the landing
ship from 1.4km away, with an average of 10% error in distance in ideal conditions.
Performance in inclement weather is also tested, only being able to start measuring from
around 400m with similar error rates afterwards