Authors :
Rithika Grace R; Vaishnavi H; Angelin Ponrani M
Volume/Issue :
Volume 9 - 2024, Issue 3 - March
Google Scholar :
https://tinyurl.com/fa93fxxf
Scribd :
https://tinyurl.com/5a5zrfch
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24MAR1535
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This project presents a cutting-edge
autonomous navigation system designed to enhance
spatial understanding and object recognition for vehicles.
Equipped with cameras on both the left and right sides,
by capturing comprehensive view of the surroundings,
utilizing stereo vision for crucial depth information. The
integration of Mobile Net and YOLO (You Only Look
Once) algorithms is central to achieving real-time object
detection and recognition. Mobile Net is employed for
efficient feature extraction, ensuring optimal
computational efficiency. Simultaneously, YOLO plays a
pivotal role in rapid and accurate identification of objects
within the captured images, contributing to the
robustness of spatial understanding crucial for
autonomous navigation. The result is a comprehensive
and reliable autonomous navigation system, showcasing
the effectiveness of combining cutting-edge technologies
for improved real time decision making.
Keywords :
YOLO, Mobile Net, Stereo Vision, Autonomous Navigation.
This project presents a cutting-edge
autonomous navigation system designed to enhance
spatial understanding and object recognition for vehicles.
Equipped with cameras on both the left and right sides,
by capturing comprehensive view of the surroundings,
utilizing stereo vision for crucial depth information. The
integration of Mobile Net and YOLO (You Only Look
Once) algorithms is central to achieving real-time object
detection and recognition. Mobile Net is employed for
efficient feature extraction, ensuring optimal
computational efficiency. Simultaneously, YOLO plays a
pivotal role in rapid and accurate identification of objects
within the captured images, contributing to the
robustness of spatial understanding crucial for
autonomous navigation. The result is a comprehensive
and reliable autonomous navigation system, showcasing
the effectiveness of combining cutting-edge technologies
for improved real time decision making.
Keywords :
YOLO, Mobile Net, Stereo Vision, Autonomous Navigation.
