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All Journal Jurnal Teknologi Perikanan dan Kelautan Indonesian Journal of Electronics and Instrumentation Systems Majalah Ilmiah Teknologi Elektro Prosiding SNATIKA Vol 01 (2011) e-Jurnal Arus Elektro Indonesia Emitor: Jurnal Teknik Elektro JURNAL NASIONAL TEKNIK ELEKTRO TELKA - Telekomunikasi, Elektronika, Komputasi dan Kontrol Jurnal Mnemonic INAJEEE (Indonesian Journal of Electrical and Electronics Engineering) Journal of Applied Computer Science and Technology (JACOST) Majalah Ilmiah Teknologi Elektro
Dedy Wahyu Herdiyanto
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Jember
Agriculture, Biological Sciences & Forestry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering Library & Information Science

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Journal : Indonesian Journal of Electronics and Instrumentation Systems

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Integrasi Robot Lengan Beroda Holonomic dan Pengindraan Visual Menggunakan Yolov5 untuk Pemilah Sampah Chaidir, Ali Rizal; Herdiyanto, Dedy Wahyu; Anam, Khairul
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems) Vol 15, No 1 (2025): April
Publisher : IndoCEISS in colaboration with Universitas Gadjah Mada, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/ijeis.103301

Abstract

The issue of waste management has become a critical topic, particularly in the sorting process, which relies on human labor and poses hygiene risks and inaccuracy. Several technologies have been explored to address this problem, including robotic arms with visual sensing, which are widely used but face challenges such as limited working areas and relatively complex installation processes. This study develops a waste-sorting robot based on a holonomic-wheeled robot integrated with visual sensing and the YOLOv5 algorithm for waste classification. The robot is equipped with a vacuum gripper for waste pickup and placement, as well as sensors for navigation and position control. Tests were conducted on four types of waste: bottles, leaves, metals, and paper. The results demonstrate a classification accuracy rate of 100%, with an average waste placement success rate of 90% for leaves and paper, and 80% for bottles, influenced by the surface characteristics of the waste and the consistency of the robot's positioning. This robotic system offers enhanced efficiency and accuracy compared to manual methods, although there remains room for improvement in the gripping mechanism and synchronization of the robot's movements. Overall, the robot system shows performance with accuracy above 80% with a wider working area than using a robot arm.
Co-Authors Afirst Rosa Hariyantin Alfian, Freska Meliniar Ali Rizal Chaidir Anam, M. Khairul Andrika, Arip Andrita Ceriana Eska Atmaja, Daris Irfan Cahyono, Yusuf Fani Dwi Catur Suko Sarwono Daris Irfan Atmaja Dimas Ardiansyah Dodi Setiabudi Felayati, Akbar GAMMA ADITYA RAHARDI Ghozali, Moch Guido Dias Kalandro Gunawan, Ekky Yonathan Hasanur Mohammad Firdausi I’zaaz Irfanianingrum Immawan Wicaksono Ivanda, Dio Ferrel Laagu, M. Asnoer Moch. Gozali Muh Asnoer Laagu Muh. Asnoer Laagu Nuryanto, Deka Rachmad Pirnadi, Irgy Syahputra Septriandi Wirayoga Sumardi Sumardi Triwahju Hardianto Wahyu Muldayani Widjonarko Widya Cahyadi