Detecting Obstacles on Railroads Using Computer Vision on UAVs
Aryan Anand, Nikhil Krishna, Nikolaos Vitzilaios
Abstract
Obstacles on railroads significantly increase the risk of traveling with a lot of train accidents caused by undetected obstacles. The obstacles disturb both the shipments of goods and the transportation of people leading to delays and damage which then result in substantial financial losses. Following natural disasters, manually locating and removing obstacles is not only time-consuming but also hazardous for the personnel involved. To address these challenges, this paper proposes an object detection system that can be implemented on an aerial drone to detect obstacles on the railway. This approach aims to enhance railway safety, reduce costs, and ensure the timely delivery of essential goods such as food and medical supplies during emergencies.
BibTeX
@inproceedings{iros2025_detectingobstacl,
title = {Detecting Obstacles on Railroads Using Computer Vision on UAVs},
author = {Aryan Anand and Nikhil Krishna and Nikolaos Vitzilaios},
booktitle = {IROS 2025},
year = {2025}
}