Deteksi Objek, Sistem Peringatan, dan Navigasi Pada Nano Drone Quadcopter Berbasis Komputer

Rahmansyah, Muhammad Faris (2025) Deteksi Objek, Sistem Peringatan, dan Navigasi Pada Nano Drone Quadcopter Berbasis Komputer. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Teknologi telah berkembang pesat dan semakin canggih dalam pengembangannya. Seiring berjalannya waktu dan berkembangnya teknologi di era modern ini, teknologi seperti drone quadcopter, kamera, dan mikrokontroler menjadi semakin terintegrasi dengan berbagai macam pengaplikasian dan implementasi. Proyek ini mengekplorasi sebuah implementasi di mana drone berukuran kecil bernama Crazyflie 2.1 dapat bekerja di dalam ruangan, menangkap citra menggunakan modul atau deck perluasannya yang disebut AI-deck 1.1, dan memberikan peringatan berupa bunyi alarm dari sebuah alat atau rangkaian yang terintegrasi dengan mikrokontroler ESP32. Sistem drone ini dipusatkan ke dalam sebuah komputer atau laptop di mana sebagian besar atau inti dari kinerja masing-masing fungsionalitas dilakukan untuk memberikan kinerja sistem yang lebih canggih, menjadikan sistem drone ini sebagai berbasis komputer atau off-board. Fungsionalitas-fungsionalitas ini meliputi implementasi kontrol seperti kontroler PID pada drone, deteksi objek menggunakan model CNN berupa YOLOv5, pemrosesan citra menggunakan library OpenCV, dan sistem alarm atau peringatan melalui ESP32 menggunakan metode IoT.
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Technology has developed rapidly and is increasingly sophisticated in its development. As time goes by and technology develops in this modern era, technologies such as quadcopter drones, cameras, and microcontrollers are becoming increasingly integrated with various applications and implementations. This project explores an implementation where a small drone called Crazyflie 2.1 can work indoors, capture images using its extension module or deck called the AI-deck 1.1, and provide alarm sound alerts from a device or circuit integrated with an ESP32 microcontroller. This drone system is centralized into a computer or laptop where most or the core of the performance of each functionality is done to provide more advanced system performance, making this drone system as computer-based or off-board. These functionalities include the implementation of controls such as a PID controllr on the drone, object detection using a CNN model in the form of YOLOv5, image processing using the OpenCV library, and alarm or alert system via ESP32 using the IoT method.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Berbasis Komputer, Deteksi Objek, Kontrol Drone, Pemrosesan Citra, Sistem Peringatan, Alert System, Drone Control, Image Processing, Object Detection, Off-board
Subjects:	T Technology > TA Engineering (General). Civil engineering (General) > TA1573 Detectors. Sensors T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques. Image analysis--Data processing. T Technology > TA Engineering (General). Civil engineering (General) > TA1650 Face recognition. Optical pattern recognition. T Technology > TA Engineering (General). Civil engineering (General) > TA174 Computer-aided design. T Technology > TA Engineering (General). Civil engineering (General) > TA593.35 Instruments, cameras, etc. T Technology > TJ Mechanical engineering and machinery > TJ1058 Rotors T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. T Technology > TJ Mechanical engineering and machinery > TJ211.4 Robot motion T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL589.2.N3 Navigation computer T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL776 .N67 Quadrotor helicopters--Automatic control U Military Science > UG1242 Drone aircraft--Control systems. (unmanned vehicle)
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Computer Engineering > 90243-(S1) Undergraduate Thesis
Depositing User:	Muhammad Faris Rahmansyah
Date Deposited:	03 Feb 2025 02:47
Last Modified:	03 Feb 2025 02:47
URI:	http://repository.its.ac.id/id/eprint/117596

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