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All Journal Jurnal Elkolind : Jurnal Elektronika dan Otomasi Industri Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Adi Rahmad Ramadhan
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Control & Systems Engineering Electrical & Electronics Engineering Engineering Mechanical Engineering

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Penerapan Harris Corner Detection dan YOLOv5 pada Kamera Stereo Vision untuk Estimasi Jarak Robot Sepak Bola Beroda KRSBI-B Adi Rahmad Ramadhan; Khumaidi, Agus; Mustika Kurnia Mayangsari; Mat Syai’in; Imam Sutrisno; Aulia Rahma Annisa
Jurnal Elektronika dan Otomasi Industri Vol. 12 No. 1 (2025): Vol 12 No 1 (Mei 2025): Jurnal Elkolind Vol 12 No 1 (Mei 2025)
Publisher : Program Studi Teknik Elektronika Politeknik Negeri Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33795/elkolind.v12i1.7254

Abstract

This research enhances the performance of a wheeled soccer robot in the RoboCup Middle Size League (KRSBI-B) by integrating Stereo Vision cameras, YOLOv5, and Harris Corner Detection for precise distance estimation and object detection. The objective is to improve the robot's ability to accurately recognize and measure the distance of objects, particularly the ball and opposing robots. Using image processing, the system significantly enhances real-time object detection, improving decision-making during the match. The YOLOv5 algorithm, trained with 4,000 labeled images, achieved impressive accuracy with confidence levels up to 0.99 for ball detection at 250 cm. Results show strong correlations between high-confidence detections and accurate distance estimations, enabling effective responses to dynamic match situations. This system provides a competitive edge, improving responsiveness, adaptability, and gameplay strategies, supporting its application in real-world robotic competitions.
The Calibration System with Color Threshold Using Stereo Camera on Wheeled Soccer Robot : Sistem Kalibrasi Dengan Color Threshold Menggunakan Kamera Stereo Pada Robot Sepak Bola Beroda Sholahuddin Muhammad Irsyad; Agus Khumaidi; Ryan Yudha Adhitya; Adi Rahmad Ramadhan; Dhika Arya Pratama
Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer Vol. 5 No. 3 (2025): November: Jurnal Ilmiah Teknik Mesin, Elektro dan Komputer
Publisher : Lembaga Pengembangan Kinerja Dosen

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.51903/juritek.v5i3.6041

Abstract

This study proposes a Color Threshold-based object detection and calibration system using an Orbbec Astra Pro Plus Stereo Vision camera on a wheeled soccer robot (KRSBI-B) to improve the accuracy and efficiency of real-time ball detection. The camera calibration process is performed using the built-in automatic feature of the Orbbec Astra OpenNI SDK, without manual calibration. Validation results show that the camera depth system has a high level of accuracy with a maximum error of 2% at a distance of 50 cm and an average error of 1.73%, making it suitable for use in object distance estimation. The HSV (Hue, Saturation, Value)-based Color Threshold method was calibrated interactively using color sliders with an optimal range of Hue (5–20°), Saturation (120–255), and Value (100–255). Testing was conducted under synthetic lighting conditions of 500 lux with a distance variation of 50–300 cm. The best results were obtained at a distance of 250 cm, with 0% measurement error and full detection on binary images. The system also showed high stability at distances of 100–300 cm with an average error of only 0.63%, while objects were not detected at a distance of 50 cm due to the camera's field of view limit. This approach provides high processing speed, good detection stability, and low computational load compared to deep learning-based methods. The integration of stereo calibration and the HSV method results in an efficient, accurate, and adaptive vision system, making it highly suitable for real-time applications on wheeled soccer robots.
Co-Authors Agus Khumaidi Agus Khumaidi Aulia Rahma Annisa Dhika Arya Pratama Imam Sutrisno Mat Syai’in Mustika Kurnia Mayangsari Ryan Yudha Adhitya Sholahuddin Muhammad Irsyad