@inproceedings{fe0fd4a4947548ed838da142cea37593,
title = "Barrelyzer: Design and Implementation of a Low-Cost Tank Barrel Inspection System",
abstract = "Maintaining confined spaces such as 10 cm barrels and pipes is a challenging task to perform without the use of intelligent systems. However, these devices are high-priced and require special training for the operators. Hence, the present paper proposes the design of a low-cost cannon barrel inspection robot. An important factor to consider in the design is the rifling of the cannon barrels. As a result, the robot was implemented and able to navigate on a simulated environment through rifling, measuring the position of the robot with an error of 4\% with a confidence level of 99\% and detecting defects using Convolutional Neural Networks with an F1-Score of 82.70\% using AdamW optimizer.",
keywords = "Artificial Intelligence, Computer Vision, Inspection System",
author = "Franco Rivadeneira and Diego Godinez and Daniela Carcausto and Sebastian Ruiz and Bruno Ivazeta and Diego Quiroz and Jose Balbuena",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; International Conference on Computer Science, Electronics and Industrial Engineering, CSEI 2023 ; Conference date: 06-11-2023 Through 10-11-2023",
year = "2024",
doi = "10.1007/978-3-031-69228-4\_35",
language = "English",
isbn = "9783031692277",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "531--545",
editor = "Garcia, \{Marcelo V.\} and Carlos Gord{\'o}n-Gallegos and Asier Salazar-Ram{\'i}rez and Carlos Nu{\~n}ez",
booktitle = "Proceedings of the International Conference on Computer Science, Electronics and Industrial Engineering (CSEI 2023) - Advances in Computer Sciences - Exploring Innovations at the Intersection of Computing Technologies",
}