Algorithmic solution and simulation results for vision-based autonomous mode of a planetary rover

Abstract

A vision based navigation (VBN) system is chosen as a basic tool to support autonomous operations of a planetary rover during space missions. The rover equipped with a stereo vision system and perhaps a laser ranging device shall be able to maintain a high level of autonomy under various illumination conditions and with little a priori information about the underlying scene. Within the LEDA Moon exploration project currently under focus by the European Space Agency, in autonomous mode the rover should perform on-board absolute localization, digital elevation model (DEM) generation, obstacle detection and relative localization, global path planning and execution. Focus of this paper is to simulate some of the path planning and path execution steps. Using a laboratory terrain mockup and an accurate camera mounting device, stereo image sequences are used for 3D scene reconstruction, risk map generation, local path planning, and position update by landmarks tracking. It is shown that standalone landmark tracking is robust enough to give navigation data for further stereoscopic reconstruction of the surrounding terrain. Iterative tracking and reconstruction leads to a complete description of the rover path and its surrounding with an accuracy high enough to meet the specifications for unmanned space exploration.