SISTEM PENDETEKSI TARGET BERDASARKAN WARNA PADA AUTONOMOUS ROBOT GUN (ARO-GUN)

Yunita Septiyanda (Teknik Elektro, Institut Teknologi Sumatera)
Ali Muhtar (Institut Teknologi Sumatera)
Purwono Prasetyawan (Institut Teknologi Sumatera)

INJECTION: Indonesian Journal of Vocational Mechanical Engineering
Vol 2 No 2 (2022): Agustus 2022

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.