This talk will focus on the Advanced Concepts Team (ACT) of the European Space Agency and its current research projects, mainly focusing on the areas of Artificial Intelligence and Robotics.

The ACT has been working on evolving Artificial Neural Networks (ANNs) for space applications as a first step to add autonomy to future spacecraft operations. These neurocontrollers can be seen as black- boxes translating inputs (position, attitude and velocities) to control outputs (thrusters), substituting hand- coded control laws. In this paper we show that evolved ANNs can be used to control one or more spacecrafts in an environment simulating zero friction and tidal gravity.

The first application considered is the autonomous docking of a spacecraft. Autonomous docking is defined as one spacecraft approaching another, with hard constraints on the final position, the final speed (usually very close to zero) and the final attitude of the spacecraft. An ANN representation is used and evolved using PaGMO, an open source software platform for global optimization of unconstrained problems developed by the ACT.

This talk tries to explain the problems of autonomous docking, the approach chosen by the ACT and will present current research and results.