José Luís Henriques da Silva
Duration: 2023 – 2025
Cised team members
Serafim Oliveira
Rui Pedro Duarte
José Luís Abrantes
Paulo Vaz
João Menoita
Unmanned Aerial Vehicles (UAVs) can be used to monitor activities and offer technological solutions in various industrial sectors.
Applying machine vision algorithms to UAVs allows vehicles to understand and interact with the surrounding environment more intelligently. They can identify and avoid obstacles, make navigation decisions based on the collected visual information, and even perform complex tasks such as following predetermined routes or recognizing specific objects.
However, artificial vision has challenges such as the need to deal with changing lighting conditions, changing weather conditions and the presence of complex and moving objects. Machine vision algorithms need to be robust enough to handle these situations and provide accurate and reliable results.
Furthermore, it is important to perform rigorous validation and testing of machine vision algorithms under different scenarios and conditions to ensure that they are robust enough before being deployed in practical applications.
This project intends to implement this technology in industrial environments, namely in precision positioning (Vision Positioning System – VPS) and automated inspection.
The use of UAVs equipped with VPS and automated inspection systems allows real-time monitoring of various industrial activities, such as detecting chemical leaks, identifying risk areas, monitoring production flow, visual quality control, among others.
Data collected by UAVs or sensors can be processed in real time and provide valuable information for decision making and ensuring safety and compliance in industrial environments.