The line follower robot is a mobile robot which can navigate and traverse to another place by following a trajectory which is generally in the form of black or white lines. This robot can also assist human in carrying out transportation and industrial automation. However, this robot also has several challenges with regard to the calibration issue, incompatibility on wavy surfaces, and also the light sensor placement due to the line width variation. Robot vision utilizes image processing and computer vision technology for recognizing objects and controlling the robot motion. This study discusses the implementation of vision based line follower robot using a camera as the only sensor used to capture objects. A comparison of robot performance employing different CPU controllers, namely Raspberry Pi and Jetson Nano, is made. The image processing uses an edge detection method which detect the border to discriminate two image areas and mark different parts. This method aims to enable the robot to control its motion based on the object captured by the webcam. The results show that the accuracies of the robot employing the Raspberry Pi and Jetson Nano are 96% and 98%, respectively.


    Access

    Download


    Export, share and cite



    Title :

    Comparative Study of Computer Vision Based Line Followers Using Raspberry Pi and Jetson Nano


    Contributors:

    Publication date :

    2021-12-30


    Remarks:

    doi:10.17529/jre.v17i4.21324
    Jurnal Rekayasa Elektrika; Vol 17, No 4 (2021) ; 2252-620X ; 1412-4785



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



    A Low-Cost Embedded Car Counter System by using Jetson Nano Based on Computer Vision and Internet of Things

    Othman, Nashwan Adnan / Saleh, Zahraa Zakariya / Ibrahim, Bishar Rasheed | IEEE | 2022


    Multi-band sub-GHz technology recognition on NVIDIA’s Jetson Nano

    Fontaine, Jaron / Shahid, Adnan / Elsas, Robbe et al. | IEEE | 2020


    Facial Mask Detection and Energy Monitoring Dashboard Using YOLOv5 and Jetson Nano

    binti Amir Hamzah, Nur Asyiqin / bin Abd Ghani, Hadhrami / Al-Selwi, Hatem Fahd et al. | Springer Verlag | 2022

    Free access

    Autonomous Robot System Based on Room Nameplate Recognition Using YOLOv4 Method on Jetson Nano 2GB

    Cahyo, Muhammad Pandu Dwi / Utaminingrum, Fitri | BASE | 2022

    Free access

    Autonomous Delivery Vehicle Using Raspberry Pi and Computer Vision

    Ravindran, Vijay / Chandrika, S. / Ponraj, Ram Prakash et al. | Springer Verlag | 2023