EndeAR

Energy-efficient, data-driven UAS trajectory planning considering macro- and micrometeorological boundary conditions

The collaborative project EndeAR between Hochschule München and TU Dresden develops a data-driven system for energy-efficient calculation of drone flight routes, which processes weather and sensor data. A modular data pipeline is being created, which prepares, processes, and provides various data sources for determining energy-optimal routes for flight route optimization.

In the project ‘Energy-efficient, data-driven UAS trajectory planning taking into account macro- and micrometeorological boundary conditions’, EndeAR for short, the cooperation network consisting of Munich University of Applied Sciences and Dresden University of Technology aims to develop a data-based system for determining energy-efficient flight routes for the drone traffic of the future. To this end, the research project is developing a data processing system that fuses sensor data from drones with weather information in order to determine and ultimately pre-calculate energy-optimised routes. Sensitivity analyses are used to determine safe flight areas in different wind conditions. The long-term goal is a nationwide map with efficient flight routes for autonomous UAS in order to optimise traffic based on real-time data. HM is developing a modular data pipeline that processes a wide variety of data in order to make it available to the calculation algorithms for energy-optimised flight routes. The research questions that arise here are:

• Which meteorological data and flight measurement data are necessary in terms of flight physics for an energy-optimised trajectory calculation?
• What properties must these data have?
• How can micro- and macro-meteorological data sets and flight measurement data be pre-processed in a data pipeline in such a way that they can be used for trajectory calculation?

The solution approach includes analysing the influence of the different data on flight physics and determining the resulting requirements. The data pipeline is developed on a modular basis so that individual components can be easily exchanged for future extensions.