Potholes Detection Using Yolo Algorithms and Their Integration Into Gazebo Simulation

Road cavities, often called potholes, pose a major problem for our transportation infrastructure, causing accidents, costly repairs, and traffic jamming. This study shows using a computer vision technique called You Only Look Once (YOLO) to find potholes on roads. YOLO is proficient and efficient for realtime object detection. The researchers want to see which version of YOLO is more effective in object analysis in pictures and videos. We'll be comparing YOLOv5, YOLOv7, and YOLOv8, thereby also setting up the system in Gazebo simulated environment. By carefully analyzing the results, we aim to understand the advantages and disadvantages of each YOLO version. This will help us see the most useful ones for finding potholes when managing and maintaining roads.

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Publication Details

Published
2024-11-21
DOI
https://doi.org/10.1109/crc63701.2024.10949894
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.35
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article

Potholes Detection Using Yolo Algorithms and Their Integration Into Gazebo Simulation

Tanazzah Rehman, M. Hassan Tanveer, Zainab Fatima, Abdullah Shah et al.
1 citations
Anomaly Detection Techniques and Applications
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article

Potholes Detection Using Yolo Algorithms and Their Integration Into Gazebo Simulation

Tanazzah Rehman, M. Hassan Tanveer, Zainab Fatima, Abdullah Shah, M. Siddique, M. Farrukh Shahid, Razvan Cristian Voicu
article en
1 citations

Abstract

Road cavities, often called potholes, pose a major problem for our transportation infrastructure, causing accidents, costly repairs, and traffic jamming. This study shows using a computer vision technique called You Only Look Once (YOLO) to find potholes on roads. YOLO is proficient and efficient for realtime object detection. The researchers want to see which version of YOLO is more effective in object analysis in pictures and videos. We'll be comparing YOLOv5, YOLOv7, and YOLOv8, thereby also setting up the system in Gazebo simulated environment. By carefully analyzing the results, we aim to understand the advantages and disadvantages of each YOLO version. This will help us see the most useful ones for finding potholes when managing and maintaining roads.

NED University of Engineering and Technology (PK), Kennesaw State University (US), National University of Computer and Emerging Sciences (PK)
Openalex Percentile: Top 29%
Anomaly Detection Techniques and Applications
0.35
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