scholarly journals Design and Implementation of Computer Vision Based Autonomous Vehicle Prototype

2022 ◽  
Author(s):  
Emre DANDIL ◽  
Bilal ARAL
Keyword(s):  
Computer Vision ◽  
Autonomous Vehicle ◽  
Design And Implementation

scholarly journals Computer vision based obstacle detection and target tracking for autonomous vehicles

2021 ◽  
Vol 336 ◽  
pp. 07004
Author(s):  
Ruoyu Fang ◽  
Cheng Cai
Keyword(s):  
Neural Network ◽  
Computer Vision ◽  
Deep Learning ◽  
Target Tracking ◽  
Real Time ◽  
Autonomous Vehicles ◽  
Autonomous Vehicle ◽  
Obstacle Detection ◽  
Pid Algorithm ◽  
Deep Learning Neural Network

Obstacle detection and target tracking are two major issues for intelligent autonomous vehicles. This paper proposes a new scheme to achieve target tracking and real-time obstacle detection of obstacles based on computer vision. ResNet-18 deep learning neural network is utilized for obstacle detection and Yolo-v3 deep learning neural network is employed for real-time target tracking. These two trained models can be deployed on an autonomous vehicle equipped with an NVIDIA Jetson Nano motherboard. The autonomous vehicle moves to avoid obstacles and follow tracked targets by camera. Adjusting the steering and movement of the autonomous vehicle according to the PID algorithm during the movement, therefore, will help the proposed vehicle achieve stable and precise tracking.

Image Capture Board for The PC

1995 ◽  
Vol 32 (3) ◽  
pp. 235-255
Author(s):  
T. David Binnie ◽  
I. Reading
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Personal Computer ◽  
Low Cost ◽  
Random Access ◽  
Image Data ◽  
Image Capture ◽  
Design And Implementation

Image capture board for the PC We report the design and implementation of a low cost, image capture board for an IBM type personal computer. The board is particularly suited to computer vision education. The board provides: image capture at video rate, random access to xy addressable image data, and options for on-board image processing hardware.

scholarly journals SEMI-OTOMATIS SISTEM PENGEREMAN AUTONOMOUS VEHICLE MENGGUNAKAN PNEUMATIK SILINDER BERBASIS MIKROKOTROLLER

2021 ◽  
Vol 16 (2) ◽  
pp. 1
Author(s):  
Teguh Arifianto ◽  
Royyan Ghozali ◽  
Akhwan Akhwan ◽  
Sunardi Sunardi ◽  
Willy Artha Wirawan
Keyword(s):  
Computer Vision ◽  
Autonomous Vehicle

Autonomous vehicle merupakan moda transportasi masa depan yang menerapkan imageprocessing dan computer vision untuk pengenalan objek maupun kendali pada motor. Transportasiini dapat beroperasi sendiri sehingga kendaraan ini mengutamakan keamanan dalam berkendara.Jika pada kendaraan konvensional, sistem pengereman dikendalikan oleh pengendara. Namun, padakendaraan autonomous, sistem pengereman akan bekerja pada keadaan tertentu. Penelitian inimemodifikasi pengereman mekanik yang ada pada kendaraan autonomous agar dapat bekerja secarasemi otomatis dengan menggunakan aktuator pneumatik silinder berukuran 50x50mm. Selain itu,penelitian ini juga menggunakan sensor warna pixycam dan micro lidar vl53l0x sebagai input padamikrokontroller arduino. Input pada mikrokontroller arduino ini menjadi parameter perintah untukmengaktifkan selenoid valve agar udara bertekenan dapat menggerakkan pneumatik silinder. Hasildari penelitian ini adalah pemakaian silinder pneumatik berukuran 50x50mm dapat menarik pedalrem pada sarana autonomous dengan tangki udara bervolume 0,16m3 dan tekanan sebesar 6 bar.

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