Intelligent Mobile Robots are increasingly used in unstructured domains; one particularly challenging example for this is, planetary exploration. The preparation of according missions is highly non-trivial, especially as it is difficult to carry out realistic experiments without, very sophisticated infrastructures. In this paper, we argue that, the, Unified System for Automation and Robot Simulation (USARSim) offers interesting opportunities for research on planetary exploration by mobile robots. With the example of work on terrain classification, it, is shown how synthetic as well as real world data, from Mars call be used to test an algorithm's performance in USARSim. Concretely, experiments with an algorithm for the detection of negotiable ground oil a, planetary surface are presented. It is shown that the approach performs fast; and robust on planetary surfaces.
Proceedings details: Lecture Notes in Computer Science (LNCS), 2009, Volume 5399, Volume DOI:10.1007/978-3-642-02921-9, Sublibrary S7 - Lecture Notes in Artificial Intelligence, editors R. Goebel, J. Siekmann, and W.Wahlster. Conference paper DOI: 10.1007/978-3-642-02921-9_40