This lecture overviews the use of deep learning-based methods and algorithms for supporting human workers in industrial environments. Deep learning algorithms are increasingly employed in the industrial sector, primarily as a part of advanced systems (e.g., intelligent machines/robots), since they offer effective and reliable solutions for ensuring human workers’ safety and reducing their stress, as… Continue reading Deep learning algorithms for intelligent support of workers
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Visual detection of elongated objects
Visual Detection of Elongated Objects: The application of computer vision to industrial inspection poses a unique challenge in identifying elongated objects that extend beyond the image frame. This lecture offers a comprehensive overview of detection and segmentation techniques, with a particular emphasis on recent advancements in deep learning-based approaches. Throughout the lecture, we delve into… Continue reading Visual detection of elongated objects
Drone imaging for industrial infrastructure inspection
This lecture overviews the use of drones for infrastructure inspection and maintenance. Various types of inspection, e.g., using visual cameras, LIDAR or thermal cameras are reviewed. Drone vision plays a pivotal role in drone perception/control for infrastructure inspection and maintenance, because: a) it enhances flight safety by drone localization/mapping, obstacle detection and emergency landing detection,… Continue reading Drone imaging for industrial infrastructure inspection
Using Artificial Intelligence and Aerial Robots for defect detection and segmentation in Industrial Inspection of Viaduct
In this lecture, Begoña Arrue, of the GRVC Robotics lab Team, will present the use Artificial intelligence algorithms and tools for inspection analytics that can facilitate the analysis of the data gathered by the aerial robotic systems developed for Industrial Inspection of Viaduct in PILOTING project. Lecture by Prof. Begoña Arrue. Link to video
Aerial Robotics for Industrial Inspection and the SIMAR project contribution
In this lecture, Miguel Ángel Trujillo, the EU SIMAR project coordinator, will present a few of the last European projects on aerial robotic inspection. Also, the talk will focus on how technology has evolved since the first one and the current state of the art. Furthermore, the SIMAR project will be presented, showing the consortium… Continue reading Aerial Robotics for Industrial Inspection and the SIMAR project contribution
Simulation of forest fires and floods
By using Unreal Engine for the creation of virtual environments we are able to simulate fire and flood scenarios with high accuracy and by using virtual UAVs we collect big virtual datasets. Mixing the virtual data with real-world data and training state-of-the-art machine learning models we hope to be able to detect real-world fires and… Continue reading Simulation of forest fires and floods