F. B. Setiawan, Eric Pratama Putra, L. Pratomo, S. Riyadi
{"title":"Implementation of line detection self-driving car using HSV method based on raspberry pi 4","authors":"F. B. Setiawan, Eric Pratama Putra, L. Pratomo, S. Riyadi","doi":"10.20895/infotel.v14i4.801","DOIUrl":null,"url":null,"abstract":"With the development of technology, especially in the field of robotics, daily human activities can be carried out with artificial intelligence. One of the artificial intelligence technologies that help ease the burden on humans, especially in terms of driving, is self-driving cars. In this case, self-driving cars have several methods with GPS systems, radar, lidar, or cameras. In this study, a self-driving car system was designed on a navigation path model using a street mark detector with an intermediary sensor, namely a camera as a vision sensor. This self-driving car system uses a prototype called an autonomous car to walk on a path which is a self-driving car navigation direction based on the detected line to be able to detect camera sensors that process line images from the camera using HSV. method. In this study, a self-driving car system has been successfully designed using a microcontroller, namely Raspberry Pi 4 as a programmer and L298n motor driver, BTS7960 as a driver for a self-driving car. The Raspberry Pi 4 sends real-time images through the camera as a vision sensor which then detects a line to navigate the movement of this self-driving car. By using image processing, the resulting level of precision can reach the average value according to the direction of the self-driving car.","PeriodicalId":30672,"journal":{"name":"Jurnal Infotel","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Jurnal Infotel","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.20895/infotel.v14i4.801","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the development of technology, especially in the field of robotics, daily human activities can be carried out with artificial intelligence. One of the artificial intelligence technologies that help ease the burden on humans, especially in terms of driving, is self-driving cars. In this case, self-driving cars have several methods with GPS systems, radar, lidar, or cameras. In this study, a self-driving car system was designed on a navigation path model using a street mark detector with an intermediary sensor, namely a camera as a vision sensor. This self-driving car system uses a prototype called an autonomous car to walk on a path which is a self-driving car navigation direction based on the detected line to be able to detect camera sensors that process line images from the camera using HSV. method. In this study, a self-driving car system has been successfully designed using a microcontroller, namely Raspberry Pi 4 as a programmer and L298n motor driver, BTS7960 as a driver for a self-driving car. The Raspberry Pi 4 sends real-time images through the camera as a vision sensor which then detects a line to navigate the movement of this self-driving car. By using image processing, the resulting level of precision can reach the average value according to the direction of the self-driving car.
随着技术的发展,特别是在机器人领域,人类的日常活动可以用人工智能进行。自动驾驶汽车是有助于减轻人类负担的人工智能技术之一,尤其是在驾驶方面。在这种情况下,自动驾驶汽车有几种带有GPS系统、雷达、激光雷达或摄像头的方法。在本研究中,在导航路径模型上设计了一个自动驾驶汽车系统,该系统使用带有中间传感器的路标检测器,即作为视觉传感器的摄像头。该自动驾驶汽车系统使用称为自动驾驶汽车的原型在作为基于检测到的线路的自动驾驶汽车导航方向的路径上行走,从而能够检测使用HSV处理来自摄像机的线路图像的摄像机传感器。方法在本研究中,使用微控制器,即Raspberry Pi 4作为程序员和L298n电机驱动器,BTS7960作为自动驾驶汽车的驱动器,成功地设计了一个自动驾驶汽车系统。Raspberry Pi 4通过摄像头作为视觉传感器发送实时图像,然后检测一条线来导航这款自动驾驶汽车的运动。通过使用图像处理,所得到的精度水平可以根据自动驾驶汽车的方向达到平均值。