Parasdyo, Fajar Luhung (2019) Vision System untuk Identifikasi Shagai pada ABU Robocon 2019. Other thesis, Institut Teknologi Sepuluh Nopember.
Preview |
Text
07111540000045-Undergraduate_Theses.pdf Download (2MB) | Preview |
Abstract
ABU Robocon (Asia-Pacific Broadcasting Union Robot Contest) merupakan kontes robot tingkat Asia-Pasifik yang diselenggarakan oleh Asia-Pacific Broadcasting Union (ABU). Pada tahun 2019, ABU Robocon diselenggarakan di Mongolia dan mengangkat tema “Great Urtuu”. Pada tema ini, ada dua robot yang dipakai yaitu robot manual dan robot otomatis. Inti permainannya adalah robot manual bertugas membawa objek bernama “Gerege” melewati halang rintang, lalu memberikannya pada robot otomatis. Setelah itu, robot otomatis berjalan melewati halang rintang hingga sampai di suatu area bernama “Mountain Urtuu”, di situ robot otomatis harus menunggu robot manual untuk melempar objek bernama “Shagai”. Setiap lemparan akan menghasilkan poin sesuai dengan warna permukaan atas pada Shagai saat mendarat. Bernilai 50 poin untuk warna emas, 40 poin untuk perak, dan 20 poin untuk biru atau merah (sesuai warna tim). Setiap tim harus mendapatkan minimal 50 poin agar robot otomatis boleh melaju hingga finish. Pada tugas akhir ini dibuat vision system untuk mengidentifikasi Shagai menggunakan kamera. Sistem ini dirancang dalam dua bagian, yaitu deteksi Shagai beserta posisinya pada citra dan identifikasi warna permukaan atas Shagai menggunakan segmentasi warna. Deteksi Shagai beserta posisinya pada citra dirancang menggunakan metode Deep Learning Object Detection. Sedangkan sistem identifikasi warna permukaan atas Shagai menggunakan metode segmentasi warna dalam pengolahan citra digital. Dari hasil pengujian, sistem untuk mengidentifikasi Shagai memiliki total akurasi sebesar 91,15% untuk Shagai merah dan 90,8% untuk Shagai biru.
===============================================================================================================================
ABU Robocon (Asia Pacific Broadcasting Union Robot Contest) is an Asia-Pacific level robot contest organized by the Asia-Pacific Broadcasting Union (ABU). In 2019, ABU Robocon was held in Mongolia and raised the theme “Great Urtuu”. In this theme, there are two robots used, namely manual robots and automatic robots. The core of the game is a manual robot tasked with carrying an object called “Gerege” past the obstacle, then giving it to an automatic robot. After that, the robot automatically walks through the obstacle until it reaches an area called “Mountain Urtuu”, where the automatic robot must wait for the manual robot to throw an object named “Shagai”. Each throw will produce points according to the color of the top surface on Shagai when landing. Worth 50 points for gold, 40 points for silver, and 20 points for blue or red (according to team colors). Each team must get a minimum of 50 points so that the automatic robot can advance to the finish. In this final project, a vision system was created to identify Shagai using a camera. This system is designed in two parts, the detection of Shagai and its position on the image, and identification of the upper surface color of Shagai using color segmentation. Detection of Shagai and its position in the image is designed using the Deep Learning Object Detection method. Whereas the surface color identification system above Shagai uses the color segmentation method in digital image processing. From the test results, the system for identifying Shagai has a total accuracy of 91.15% for Shagai with red color and 90.8% for Shagai with blue color.
| Item Type: | Thesis (Other) |
|---|---|
| Additional Information: | RSE 621.367 Par v-1 2019 |
| Uncontrolled Keywords: | Vision System, Object Detection, Shagai, ABU Robocon 2019 |
| Subjects: | Q Science > QA Mathematics > QA336 Artificial Intelligence Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Fajar Luhung Parasdyo |
| Date Deposited: | 15 Mar 2023 04:05 |
| Last Modified: | 15 Mar 2023 04:05 |
| URI: | http://repository.its.ac.id/id/eprint/63766 |
Actions (login required)
 |
View Item |