Algorithmic Solution and Simulation Results for Vision-Based Autonomous Mode of a Planetary Rover

A vision based navigation (VBN) system is chosen as a basic tool to provide autonomous operations of a planetary rover during space missions. That means that 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. As it is specified in the LEDA Moon exploration project currently under focus by the European Space Agency ESA, during the autonomous mode the rover should perform the following operations: on-board absolute localization, 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. That is done with the help of a laboratory terrain mockup and a high precision camera mounting device. The following operations are performed on the basis of stereo image sequence: 3D scene reconstruction, risk map generation, local path planning, update cameras position during the motion on the basis of landmarks tracking. It is shown that standalone tracking using automatically identified landmarks 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.