Intelligent autonomous drone

Drones are used in multiple industries such as military, construction, maritime and more. It has allowed many companies to work more efficiently while reducing the manpower labor and enhancing the worker’s safety at the same time. This technology has been constantly evolving and improving. Now, with...

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Bibliographic Details
Main Author: Loon, Zi Jian
Other Authors: Wen Bihan
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/167295
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1672952023-07-07T17:54:29Z Intelligent autonomous drone Loon, Zi Jian Wen Bihan School of Electrical and Electronic Engineering Satellite Research Centre bihan.wen@ntu.edu.sg Engineering::Electrical and electronic engineering::Computer hardware, software and systems Drones are used in multiple industries such as military, construction, maritime and more. It has allowed many companies to work more efficiently while reducing the manpower labor and enhancing the worker’s safety at the same time. This technology has been constantly evolving and improving. Now, with the help of Artificial Intelligence (AI) algorithm, drones will be able to perform more automated tasks and be always adaptive to its environment which includes collision avoidance. In this project, I aimed to develop an autonomous drone application to perform inspection tasks. To achieve this objective, I will develop a Proportional-Integral-Derivative (PID)-based flight control algorithm for efficient navigation and tracking purposes. Then, I will evaluate and integrate some of the state-of-the-art AI object detection algorithms such as You-Only-Look-Once (YOLO). The AI will be able to detect structural defects that are commonly found such as cracks and corrosions. The PID controller’s parameters were optimized through trial and errors by real flight tests. It was designed to track defects detected by the object detection algorithm and maintain its position so that picture can be clearly captured by the drone. All image processing and computation will be leveraging the NVIDIA Jetson NX edge onboard computer installed onto the DJI drone. Bachelor of Engineering (Electrical and Electronic Engineering) 2023-05-26T13:22:18Z 2023-05-26T13:22:18Z 2023 Final Year Project (FYP) Loon, Z. J. (2023). Intelligent autonomous drone. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/167295 https://hdl.handle.net/10356/167295 en A3251-221 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering::Computer hardware, software and systems
spellingShingle Engineering::Electrical and electronic engineering::Computer hardware, software and systems
Loon, Zi Jian
Intelligent autonomous drone
description Drones are used in multiple industries such as military, construction, maritime and more. It has allowed many companies to work more efficiently while reducing the manpower labor and enhancing the worker’s safety at the same time. This technology has been constantly evolving and improving. Now, with the help of Artificial Intelligence (AI) algorithm, drones will be able to perform more automated tasks and be always adaptive to its environment which includes collision avoidance. In this project, I aimed to develop an autonomous drone application to perform inspection tasks. To achieve this objective, I will develop a Proportional-Integral-Derivative (PID)-based flight control algorithm for efficient navigation and tracking purposes. Then, I will evaluate and integrate some of the state-of-the-art AI object detection algorithms such as You-Only-Look-Once (YOLO). The AI will be able to detect structural defects that are commonly found such as cracks and corrosions. The PID controller’s parameters were optimized through trial and errors by real flight tests. It was designed to track defects detected by the object detection algorithm and maintain its position so that picture can be clearly captured by the drone. All image processing and computation will be leveraging the NVIDIA Jetson NX edge onboard computer installed onto the DJI drone.
author2 Wen Bihan
author_facet Wen Bihan
Loon, Zi Jian
format Final Year Project
author Loon, Zi Jian
author_sort Loon, Zi Jian
title Intelligent autonomous drone
title_short Intelligent autonomous drone
title_full Intelligent autonomous drone
title_fullStr Intelligent autonomous drone
title_full_unstemmed Intelligent autonomous drone
title_sort intelligent autonomous drone
publisher Nanyang Technological University
publishDate 2023
url https://hdl.handle.net/10356/167295
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