SISTEM PENDETEKSI TARGET BERDASARKAN WARNA PADA AUTONOMOUS ROBOT GUN (ARO-GUN) - Yunita Septiyanda; Ali Muhtar; Purwono Prasetyawan (Politeknik Negeri Ketapang, 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.