Earlier this year, a team from the Micro Air Vehicle Laboratory, MAVLab, of Delft University of Technology, TU Delft, competed against 13 autonomous drones and three drone racing champions at the A2RL Drone Championship in Abu Dhabi – beating them all in a historic racing first.

The victorious team’s drone was able to dominate the competition thanks to neural network-based AI control systems, originally developed by ESA’s Advanced Concepts Team (ACT) – the agency’s multidisciplinary think tank focusing on emerging technologies.

ACT’s scientific coordinator Dario Izzo explains how the collaboration started: “A few years ago, the ACT started working on neural networks for spacecraft guidance.

“Typically, in space settings, Guidance and Control are two separate systems. The Guidance part, involving different manoeuvres, is traditionally planned in detail by engineers on the ground, while the Control part is undertaken by the spacecraft itself.

“To make the system more efficient, we explored a way to combine the two in one, creating an end-to-end controller. This alternative method, called Guidance & Control Networks – G&CNets – involves all the work taking place on the spacecraft.

“Before using this method to fly real spacecraft, we needed a more accessible testing platform – this is when our collaboration with TU Delft’s MAVLab started. Our concept tested on MAVLab’s drones immediately delivered incredible results.”