IMPLEMENTASI METODE PENGOLAHAN CITRA DAN ROBOT OPERATING SYSTEM UNTUK PENDETEKSIAN LANDASAN QUADCOPTER; IMPLEMENTATION OF IMAGE PROCESSING METHOD AND ROBOT OPERATING SYSTEM TO DETECT QUADCOPTER LANDMARK

Kurniawan, Fajar, Bakhtiar Alldino

2015 | Skripsi | FMIPA

Quadcopter ability to perform an automatic landing is a crucial need for quadcopter system this time. An automatic landing capability can be used to avoid the problem if the quadcopter out of control, running out of power, or there are some problems in the system. A way to make an automatic landing system is to implement a digital image processing method to detect the landing target. Landmark detection can be applied by using OpenCV library which the shape of the landing target is a circle. This research compares Blob detection and Hough Transform methods in order to know the capabilities of these two methods. Blob Detection and Hough Transform methods are able to detect landmark object over 3 m. Blob Detection method needs 14 ms to detect landmark object, while the Hough Transform method requires longer time, it needs 363,6 ms. Landmark detection system using Hough Transform method has a 90% success rate, while the Blob Detection method has a 100% success rate. Quadcopter horizontal movement process to the landmark point has a 80% success rate, while quadcopter vertical movement process to the landmark point has a 50% success rate. Quadcopter which is used in this research is Parrot AR.Drone 2.0. All images are sampled by using AR.Drone built-in camera. Image processing was performed on the laptop which is connected to the AR.Drone’s access point. OpenCV’s library was integrated with the Robot Operating System, so that it can be used along with AR.Drone driver.

Kata Kunci : Parrot AR.Drone 2.0; OpenCV; Blob Detection; Hough Transform