Learning-based motion control of a rover on unknown ground

Abstract

This paper presents the current status and scientific approaches from the ESA project DeLeMIS. Within that, e:fs and DLR Robotics investigate state-of-the-art approaches of self-learning methods to enable improvements in planetary space missions. The main objective of DeLeMIS is the autonomous navigation of a rover on unknown terrain without human intervention. To this end, algorithms from the latest research in the Artificial Intelligence (AI) and control engineering community are used for environmental perception and behaviour control. On the one hand, the rover is supposed to learn the ground conditions of different areas and their boundaries, both through camera inputs and through the interaction of the wheels with the ground. On the other hand, the system is intended to learn the best behaviour and the most appropriate strategy for its motion and navigation across different ground surfaces, taking into account safety and robustness aspects.