Image-based autonomous landing of unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) are useful in various applications, one of which is in the field of logistics, used by e-commerce companies such as Alibaba, JD.com and Amazon. However, a limited battery capacity and an insufficiently accurate navigation satellite signal are the primary factors imped...

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Main Author: Yong, Jian Wen
Other Authors: Low Kin Huat
Format: Final Year Project
Language:English
Published: 2019
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Online Access:http://hdl.handle.net/10356/78744
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-787442023-03-04T18:38:24Z Image-based autonomous landing of unmanned aerial vehicles Yong, Jian Wen Low Kin Huat School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Unmanned aerial vehicles (UAVs) are useful in various applications, one of which is in the field of logistics, used by e-commerce companies such as Alibaba, JD.com and Amazon. However, a limited battery capacity and an insufficiently accurate navigation satellite signal are the primary factors impeding a more widespread adoption of this technology. Therefore, this project aims to develop a vision-based autonomous landing system of UAVs that can help to overcome these problems. There are two available approaches: position-based visual servoing (PBVS) and image based-visual servoing (IBVS). In this project, IBVS was selected for use due to its lower consumption of computational power and no need for precise camera calibration compared to PBVS. In addition, in contrast to PBVS, IBVS does not require an accurate estimation of the 3D parameters and it is more robust to errors in estimation. This report will discuss the reasons of choosing ArUco markers over the other types of fiducial markers. Besides that, the algorithms used for detecting the ArUco markers, written in MATLAB, will be discussed. The steps involved in the process are image binarization, boundaries extraction, quadrilaterals detection and eventually marker identification. This report will also discuss the use of Simulink in creating an IBVS model, which will be modified at a later stage to receive and send data using a custom ROS message. Simulations were carried out in the Ubuntu environment using tools like OpenCV, ROS and Gazebo. Several experiments were conducted to test the IBVS system designed, which include hovering and landing of UAV above a marker, and tracking of a moving marker with translational as well as rotational motion. The results obtained from the experiments were then analyzed. It is believed that, by implementing the design in this project, autonomous landing of UAVs and other applications such as hovering above moving targets and horizontal visual locking can be realized. Bachelor of Engineering (Mechanical Engineering) 2019-06-26T07:00:14Z 2019-06-26T07:00:14Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/78744 en Nanyang Technological University 67 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
spellingShingle Engineering::Mechanical engineering
Yong, Jian Wen
Image-based autonomous landing of unmanned aerial vehicles
description Unmanned aerial vehicles (UAVs) are useful in various applications, one of which is in the field of logistics, used by e-commerce companies such as Alibaba, JD.com and Amazon. However, a limited battery capacity and an insufficiently accurate navigation satellite signal are the primary factors impeding a more widespread adoption of this technology. Therefore, this project aims to develop a vision-based autonomous landing system of UAVs that can help to overcome these problems. There are two available approaches: position-based visual servoing (PBVS) and image based-visual servoing (IBVS). In this project, IBVS was selected for use due to its lower consumption of computational power and no need for precise camera calibration compared to PBVS. In addition, in contrast to PBVS, IBVS does not require an accurate estimation of the 3D parameters and it is more robust to errors in estimation. This report will discuss the reasons of choosing ArUco markers over the other types of fiducial markers. Besides that, the algorithms used for detecting the ArUco markers, written in MATLAB, will be discussed. The steps involved in the process are image binarization, boundaries extraction, quadrilaterals detection and eventually marker identification. This report will also discuss the use of Simulink in creating an IBVS model, which will be modified at a later stage to receive and send data using a custom ROS message. Simulations were carried out in the Ubuntu environment using tools like OpenCV, ROS and Gazebo. Several experiments were conducted to test the IBVS system designed, which include hovering and landing of UAV above a marker, and tracking of a moving marker with translational as well as rotational motion. The results obtained from the experiments were then analyzed. It is believed that, by implementing the design in this project, autonomous landing of UAVs and other applications such as hovering above moving targets and horizontal visual locking can be realized.
author2 Low Kin Huat
author_facet Low Kin Huat
Yong, Jian Wen
format Final Year Project
author Yong, Jian Wen
author_sort Yong, Jian Wen
title Image-based autonomous landing of unmanned aerial vehicles
title_short Image-based autonomous landing of unmanned aerial vehicles
title_full Image-based autonomous landing of unmanned aerial vehicles
title_fullStr Image-based autonomous landing of unmanned aerial vehicles
title_full_unstemmed Image-based autonomous landing of unmanned aerial vehicles
title_sort image-based autonomous landing of unmanned aerial vehicles
publishDate 2019
url http://hdl.handle.net/10356/78744
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