relation: https://khub.utp.edu.my/scholars/18932/
title: Tracking Control of Tello EDU Quadrotor Drone Using Image Thresholding
creator: Kasraoui, A.
creator: Bingi, K.
creator: Ibrahim, R.
creator: Omar, M.
creator: Devan, P.A.M.
creator: Prusty, B.R.
description: In many industries, it is crucial to have an efficient and precise way of monitoring objects or individuals. Drones can be used for this purpose, such as in agriculture, to observe crop growth and detect potential issues. This makes them a valuable tool in different fields, offering greater accuracy and faster data collection. This research uses image thresholding to implement a Tello EDU RoboMaster TT quadrotor drone tracking control system. The goal is for the drone to autonomously follow different line shapes, rounded at different angles, steadily and safely. The drone's camera captures the line's contours using open-source methods, which are processed using image thresholding and binary masking techniques. A control point is generated at the centre of the contours and compared to the centre of the image to guide the drone's movements in real time. The research has successfully enabled the drone to follow lines of various shapes. © 2023 IEEE.
date: 2023
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Kasraoui, A. and Bingi, K. and Ibrahim, R. and Omar, M. and Devan, P.A.M. and Prusty, B.R.  (2023) Tracking Control of Tello EDU Quadrotor Drone Using Image Thresholding.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85186981998&doi=10.1109%2fI-PACT58649.2023.10434743&partnerID=40&md5=e6c1cf990bd528d714f8659ce2cca2ea
relation: 10.1109/I-PACT58649.2023.10434743
identifier: 10.1109/I-PACT58649.2023.10434743