MAchine learning
Last week, Raúl Hernández Oliu, Tomás De Urrengoechea Cantavenera, Jaya Garcia and Oriol Bracons Escarré participated in ENGAGE 2 Data Hackathon organized by Innaxis and held in Madrid. They developed a Machine Learning model to predict the time between a runway threshold and the moment an aircraft aligns with the runway, by analyzing ADS-B data.
A Multi-Agent negotiation framework for planning conflict-free U-space scenarios The expected growth of drone traffic in both urban and rural areas calls for highly automated and scalable air traffic management solutions. U‑PLAN addresses this challenge by developing smart U‑space services that help balance airspace demand and capacity while maintaining safety and efficiency. The project introduces automated, negotiation‑based mechanisms that detect […]
The phrase ‘autopilot’ is used ubiquitously these days. Most often, it refers to executing a sequence of actions without really thinking about them, rather than its official meaning: the automatic control of steering of a ship or aerospace vehicle. While this tends to make ‘autopiloting’ seem simple and straightforward, replacing the complicated decision-making of a […]