METSIS: Hyperlocal Wind Nowcasting for U-space

The METeo Sensors in the Sky (METSIS) project, funded by SESAR’s Engage knowledge transfer network, investigated the use of drones as an aerial wind sensor network for U-space applications. The concept aims to provide accurate, lowcost and hyperlocal wind nowcasts for drones using data collected by drones themselves and the Meteo-Particle Model ...

Aerial Robotics: State-based Conflict Detection and Resolution (Detect and Avoid) in High Traffic Densities and Complexities

Purpose of Review A lot of research into decentralised, state-based conflict detection and resolution, or detect and avoid algorithms has been executed. This paper explains the essential properties of state-based conflict detection and reviews the work in the context of applications for not only manned but also unmanned aerial vehicles, where...

Geovectoring: Reducing Traffic Complexity to Increase the Capacity of UAV airspace

Both U-space in Europe, as well as UTM in the USA, develop concepts and tools for UAV airspace. Enabling highdensity operations is one of the goals of these studies. Past and recent studies have analysed which factors affect the capacity of a UAV airspace. An improved understanding of this can lead to control methods for capacity management. Two...