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All Journal INJECTION: Indonesian Journal of Vocational Mechanical Engineering
Yunita Septiyanda
Teknik Elektro, Institut Teknologi Sumatera
Control & Systems Engineering Economics, Econometrics & Finance Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering

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SISTEM PENDETEKSI TARGET BERDASARKAN WARNA PADA AUTONOMOUS ROBOT GUN (ARO-GUN) Yunita Septiyanda; Ali Muhtar; Purwono Prasetyawan
Injection: Indonesian Journal of Vocational Mechanical Engineering Vol 2 No 2 (2022): Agustus 2022
Publisher : Politeknik Negeri Ketapang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (720.068 KB) | DOI: 10.58466/injection.v2i2.671

Abstract

The low level of accuracy and precision in the process target tracking by military causing casualties because of shooting error. Shooting error can be due because of human-error like fatigue. Therefore, this study aims to design a system that can detect and lock target automatically so that shooting errors can be minimized. On the implementation, the system uses color detection, which is a part of the digital image processing method. The target image, which has been recorded by a webcam, will be processed by a Raspberry Pi 3b+ using Python and the OpenCV library. Research results shown the ARO-GUN system can perform precise detection on a predetermined target with 100% accuracy of target detection also capable of accurately detecting the target in the light intensity range of 750-1000 lux. Therefore, the ARO-GUN system has been able to meet the design goal to detect accurately so it’s can minimize shooting errors.
Co-Authors Ali Muhtar Prasetyawan, Purwono