Garuda - Garba Rujukan Digital

Pattern Recognition untuk Deteksi Posisi pada AGV Berbasis Raspberry Pi Florentinus Budi Setiawan; Franciska Amalia Kurnianingsih; Slamet Riyadi; Leonardus Heru Pratomo
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 10 No 1: Februari 2021
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

The development of technology in automation and robotics is overgrowing because of its high-efficiency level in terms of labor and time. In the warehousing system, one of the robots used is Automated Guided Vehicle (AGV). AGV is a transportation device in the form of a robot that can be controlled automatically, which functions as a carrier of goods using a navigation system to move in a predetermined direction. One of the existing AGV navigation systems is by following a line pattern on the floor. The system is inefficient because, gradually, the line pattern will wear out and can not be detected again due to the friction force of the AGV wheels itself. Therefore, it is necessary to develop an AGV navigation system to minimize these obstacles. This pattern recognition system uses a pattern placed on the building ceiling and camera as a sensor facing upwards, so that AGV can freely detect patterns. Then, the detected pattern was processed through a programmed Raspberry Pi 4 Model B. The test results show that this system can detect the position and successfully displays the coordinate point (x, y) of the AGV and will continue to run at any time until the program is changed as ordered.

Design of Audiosonic Frequency Wave Therapy Tool With Arduino Mega-Based Spectrum Analyzer Monitoring Florentinus Budi Setiawan; Daniel Danin Prasetyo; Leonardus Heru Pratomo
PROtek : Jurnal Ilmiah Teknik Elektro Vol 10, No 1 (2023): PROtek : Jurnal Ilmiah Teknik Elektro
Publisher : Program Studi Teknik Elektro Universitas Khairun

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33387/protk.v10i1.5536

As technology develops, more and more devices can produce or record sound waves. There are currently a lot of sound wave generators in use; however, the frequency output range of these generators is highly constrained. This study is being done to help doctors or the general public treat specific illnesses or disorders such as neurological disorders, headaches, and stomach digestion issues. This prototype was created using experimental or lab techniques. by running tests on the variables being utilized. The Arduino Mega 2560 microcontroller is used to operate this prototype. The Arduino Mega 2560 employs the C and C+ programming languages for its code. The Arduino Mega 2560 may be used to modify the keypad's output frequency, amplitude, and data input. This tool is designed to be able to output frequencies of 20 Hz to 20,000 Hz (human sound). In this study, it has an output in the form of frequencies produced from speakers with test frequencies, namely 200 Hz, 10 kHz, and 17 kHz

Pengenalan Tanda Arah untuk Navigasi Automatic Guided Vehicle berbasis Raspberry Pi Florentinus Budi Setiawan; Rachmat Hidayat; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 1: Februari 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i1.4959

The development of modern times in robotics and mechanization technology has increased significantly in the past few decades due to their high efficiency in time and energy. In the goods mobilization system for companies’ use, particularly the industrial and warehousing divisions, one of the robots that are used for transporting goods is an automatic guided vehicle (AGV). One of the old navigation methods in AGV is the use of a sensor to follow the line pattern on the detected object, namely the line on the floor. This method is rather ineffective because, gradually, these line pattern objects on the floor will fade caused by the effect of AGV wheels’ frictional forces, causing the camera sensor can no longer detect them. Therefore, it is necessary to improve the AGV navigation method so that it can be a sustainable innovation. This navigation method used four image objects positioned in the area traversed by the AGV robot and the camera served as a forward-facing sensor so that the AGV could detect the pattern of image objects with the help of computer vision using the OpenCV software library. The pattern of the detected image object was processed by a program designed on the Raspberry Pi 4 Model B minicomputer. The test results prove that this method can detect image objects within the camera’s field of view and successfully display the output of the image object. The system managed to recognize objects quite accurately, with parameters of 10–95 cm, and through several experiments. The analysis of the rotational speed of the front and rear wheels of the AGV was carried out using an oscilloscope and tachometer as a means of measuring wheel speed or rotation.

Metode Sederhana untuk Mengendalikan Inverter 5-Tingkat Berbasis Algoritma ¼ λ Leonardus Heru Pratomo
Jurnal Rekayasa Elektrika Vol 15, No 2 (2019)
Publisher : Universitas Syiah Kuala

The inverter with low voltage harmonics on the output side is a very interesting topic, and widely studied. One of these solutions is a 5-levels inverter: Dual Buck DC-DC Converter - H Bridge Inverter (DBC-HBI). The inverter control methods based on digital sinusoidal pulse width modulation (DSPWM) are commonly implemented by one or a half of the wavelength algorithm (λ). However, one period could be constructed by combining four algorithms by ¼ λ. In this paper, an algorithm of DSPWM based on a ¼ λ algorithm is investigated. The aim of this research is the simplest control and capacities of memory. Finally, a verification of the proposed method was carried out by the experiment in the laboratory. Based on the laboratory tests: 1 λ algorithm has a simple algorithm, but uses large memory, whereas a ¼ λ algorithm more complicated but uses less memory.

Perancangan Automated Guided Vehicle Menggunakan Penggerak Motor DC dan Motor Servo Berbasis Raspberry Pi 4 Florentinus Budi Setiawan; Yosia Yovie Christian Wibowo; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Rekayasa Elektrika Vol 18, No 2 (2022)
Publisher : Universitas Syiah Kuala

The influence of the industrial revolution 4.0 resulted in very significant changes. Many companies compete to produce robots that facilitate human work, in terms of energy and time in the process of producing goods. One of the robots being developed is the Automated Guided Vehicle (AGV), a vehicle with automatic control. AGV has high accuracy, easy maintenance, and a long operating time. This study discusses the design and implementation of AGV using 2 motors. The front motor using a servo motor is used for steering to turn right and turn left, while the rear motor in the form of a DC motor is used to regulate the speed of the AGV. The AGV movement system is controlled by computer vision. The AGV problem encountered is that the camera reading distance is close, which makes it less efficient in industrial use. This problem can be solved with a camera connected to a raspberry pi capable of capturing text and images from a distance of 100 cm. The use of computer vision makes the AGV robot easy to move. In this study, the accuracy of the movement of the AGV robot to the trajectory pattern has an average angle difference of 3.09°. The difference in the angle indicates a small error so that the AGV can operate optimally. Infield applications, this AGV is used in the manufacturing industry to move goods. Therefore, the use of AGV is needed because it has high accuracy and small error.

Penerapan Algoritma HSV pada Autonomous Car untuk Sistem Self-Driving Berbasis Raspberry Pi 4 Florentinus Budi Setiawan; Padang Ufqi Sutrisno; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Rekayasa Elektrika Vol 18, No 4 (2022)
Publisher : Universitas Syiah Kuala

Perkembangan teknologi di sektor transportasi di masa ini semakin krusial. Sehingga perusahaan berinovasi menciptakan mobil yang dapat berjalan sendiri dengan tingkat keamanan yang tinggi. Pada penelitian ini, kami merancang sistem self-driving untuk mobil RC skala 1:10 menggunakan komponen utama berupa Raspberry Pi 4 sebagai pengolahan citra untuk kendali otomatis pada autonomous car. Untuk mengatur pergerakan roda belakang dan steering menggunakan motor DC. Penelitian ini menerapkan computer vision yang dipakai untuk sistem navigasi agar dapat berjalan sesuai dengan lintasan. Permasalahan yang dijumpai pada penelitian sebelumnya adalah masih mengambil sampel lintasan terlebih dahulu yang dirasa kurang efisien karena pada jalan yang belum diambil sampelnya tidak dapat dilalui robot tersebut. Untuk memecahkan permasalahan ini maka peneliti menerapkan algoritma HSV agar dapat mengikuti lintasan secara real-time. Algoritma HSV(hue, saturation, value) merupakan sistem untuk mendeteksi tepi garis lintasan dengan memproses gambar dari kamera Raspberry Pi. Dari hasil kalibrasi nilai threshold yang digunakan adalah sebesar Hmin = 135 dan Hmax = 179, Smin = 70 dan Smax = 255, dan nilai V sebesar Vmin = 53 dan Vmax = 106 agar dapat mendeteksi jalur lintasan secara jelas, baik di dalam ruangan maupun diluar ruangan, dan HSV toleran terhadap perubahan intensitas cahaya. Itulah keuntungan dari algoritma HSV. Berdasarkan hasil pengujian dan implementasi robot ini dengan menggunakan kecerdasan buatan dapat bekerja sesuai dengan algoritma yang sudah dibuat dengan tingkat akurasi deteksi jalur yang cukup tinggi.

Metode Sederhana untuk Mengendalikan Inverter 5-Tingkat Berbasis Algoritma ¼ λ Leonardus Heru Pratomo
Jurnal Rekayasa Elektrika Vol 15, No 2 (2019)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v15i2.13642

The inverter with low voltage harmonics on the output side is a very interesting topic, and widely studied. One of these solutions is a 5-levels inverter: Dual Buck DC-DC Converter - H Bridge Inverter (DBC-HBI). The inverter control methods based on digital sinusoidal pulse width modulation (DSPWM) are commonly implemented by one or a half of the wavelength algorithm (λ). However, one period could be constructed by combining four algorithms by ¼ λ. In this paper, an algorithm of DSPWM based on a ¼ λ algorithm is investigated. The aim of this research is the simplest control and capacities of memory. Finally, a verification of the proposed method was carried out by the experiment in the laboratory. Based on the laboratory tests: 1 λ algorithm has a simple algorithm, but uses large memory, whereas a ¼ λ algorithm more complicated but uses less memory.

Perancangan Automated Guided Vehicle Menggunakan Penggerak Motor DC dan Motor Servo Berbasis Raspberry Pi 4 Florentinus Budi Setiawan; Yosia Yovie Christian Wibowo; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Rekayasa Elektrika Vol 18, No 2 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v18i2.25863

The influence of the industrial revolution 4.0 resulted in very significant changes. Many companies compete to produce robots that facilitate human work, in terms of energy and time in the process of producing goods. One of the robots being developed is the Automated Guided Vehicle (AGV), a vehicle with automatic control. AGV has high accuracy, easy maintenance, and a long operating time. This study discusses the design and implementation of AGV using 2 motors. The front motor using a servo motor is used for steering to turn right and turn left, while the rear motor in the form of a DC motor is used to regulate the speed of the AGV. The AGV movement system is controlled by computer vision. The AGV problem encountered is that the camera reading distance is close, which makes it less efficient in industrial use. This problem can be solved with a camera connected to a raspberry pi capable of capturing text and images from a distance of 100 cm. The use of computer vision makes the AGV robot easy to move. In this study, the accuracy of the movement of the AGV robot to the trajectory pattern has an average angle difference of 3.09°. The difference in the angle indicates a small error so that the AGV can operate optimally. Infield applications, this AGV is used in the manufacturing industry to move goods. Therefore, the use of AGV is needed because it has high accuracy and small error.

Penerapan Algoritma HSV pada Autonomous Car untuk Sistem Self-Driving Berbasis Raspberry Pi 4 Florentinus Budi Setiawan; Padang Ufqi Sutrisno; Leonardus Heru Pratomo; Slamet Riyadi
Jurnal Rekayasa Elektrika Vol 18, No 4 (2022)
Publisher : Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.17529/jre.v18i4.27495

Perkembangan teknologi di sektor transportasi di masa ini semakin krusial. Sehingga perusahaan berinovasi menciptakan mobil yang dapat berjalan sendiri dengan tingkat keamanan yang tinggi. Pada penelitian ini, kami merancang sistem self-driving untuk mobil RC skala 1:10 menggunakan komponen utama berupa Raspberry Pi 4 sebagai pengolahan citra untuk kendali otomatis pada autonomous car. Untuk mengatur pergerakan roda belakang dan steering menggunakan motor DC. Penelitian ini menerapkan computer vision yang dipakai untuk sistem navigasi agar dapat berjalan sesuai dengan lintasan. Permasalahan yang dijumpai pada penelitian sebelumnya adalah masih mengambil sampel lintasan terlebih dahulu yang dirasa kurang efisien karena pada jalan yang belum diambil sampelnya tidak dapat dilalui robot tersebut. Untuk memecahkan permasalahan ini maka peneliti menerapkan algoritma HSV agar dapat mengikuti lintasan secara real-time. Algoritma HSV(hue, saturation, value) merupakan sistem untuk mendeteksi tepi garis lintasan dengan memproses gambar dari kamera Raspberry Pi. Dari hasil kalibrasi nilai threshold yang digunakan adalah sebesar Hmin = 135 dan Hmax = 179, Smin = 70 dan Smax = 255, dan nilai V sebesar Vmin = 53 dan Vmax = 106 agar dapat mendeteksi jalur lintasan secara jelas, baik di dalam ruangan maupun diluar ruangan, dan HSV toleran terhadap perubahan intensitas cahaya. Itulah keuntungan dari algoritma HSV. Berdasarkan hasil pengujian dan implementasi robot ini dengan menggunakan kecerdasan buatan dapat bekerja sesuai dengan algoritma yang sudah dibuat dengan tingkat akurasi deteksi jalur yang cukup tinggi.

Title

Found 9 Documents
Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title Search

Found 9 Documents Search

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 9 Documents
Search