What is Learning to Fly ?
The importance of drones in our society is getting more and more important. Many companies are now using drones in order to realise specific missions like infrastructure inspection. The usage of drones and machines learning technologies combined is a real opportunity for all the actors of this market. This consideration is at the birth of the ISAE-Supaero’s project : learning to fly.
Learning to Fly aims at increasing the autonomy of a fixed wing drone and improve energy efficiency by benefiting from thermals. For this, we use artificial intelligence, more precisely reinforcement learning. Hence, our glider will be able to stay as long as possible in the air.
Who’s in charge of the project ?
Learning to Fly is as project that has involves many people over the years. Researchers and students have contributed to the progress of this project. People involved are from ISAE-Supaero a prestigious engineering school in Toulouse (FRANCE) that deals mainly with aeronautics. Therefore, they were able to highlight their scientific know-how not only in the field of flight mechanics but also in the field of machine learning.
At this stage, all our results are simulations on computer, this allows to test different models of artificial intelligence and thermals. The simulations are running on a homemade software. Initially, the simulator software was coded under Matlab, but for performance reasons, it was decided to recode it under C++. A detailed description of this new software, named L2F, is available in the section « Software ». An exemple of a L2F simulation is disposable in the section “Demo”.
In this website we will present the project in different headings
People : people involved in the project (Researchers and students)
Publications : Contains scientific publications related to the project.
Software : Contains a detailed description of the demonstrator as well as an explanation to how the code can be downloaded and its documentation accessed.
Demo : Contains an example of simulation and its results.