Paper Info
Title
A Robust QR and Computer Vision-Based Sensorless Steering Angle Control, Localization, and Motion Planning of Self-Driving Vehicles
Abstract
Autonomous path following has gained tremendous popularity during the last few decades. Numerous researchers have contributed to the development of highly automated navigation systems using different types of sensors and their combination. However, their proposed approaches do not provide a cost-efficient solution because of the deployment of exorbitant and sophisticated sensors, which remains a challenging problem for customized vehicles used in academic research. To overcome this issue, this study presents an economically efficient sensorless steering angle approach that employs a single camera for steering control and quick response (QR) based localization of a vehicle. Moreover, we used SONAR for object detection in a defined route to avoid possible collisions. The proposed technique combines a Probablistic Hough Transfrom for lane detection and QR codes, which helps the vehicle stay in its lane for stabilized control. To prove the efficiency of our approach, we tested it on our developed prototype vehicle named EMO. To validate the proposed approach through in-field testing, we designed a customized test track within the campus. The experimental results show the benefit of our proposed approach compared to existing methods available in the literature.
Year
DOI
Venue
2021
10.1109/ACCESS.2021.3124636
IEEE ACCESS
Keywords
DocType
Volume
Location awareness, Sensors, Three-dimensional displays, Planning, Laser radar, Cameras, Robots, Sensorless steering angle control, localization, lane detection, quick response
Journal
9
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Samia Abid101.01
Bashir Hayat200.34
Sarmad Shafique300.34
Zain Ali400.34
Bilal Ahmed500.34
Faisal Riaz611.38
Tae-Eung Sung700.34
Ki-Il Kim800.68