Ego-motion estimation of lunar rover based on vision sequence images

Lunar environment information that coming from lunar rover stereo vision system is a very important source for lunar rover. This paper presents an motion estimation algorithm that will enable lunar rover travels in unstructured lunar environment autonomously, our techniques are based on the stereo vision sequence images, firstly, matched-features aggregate are build by image processing step such as feature detection, feature tracking and feature matching, next, robust motion estimation is executed to estimate the motion initially and reject the outliers, and then, Levenberg-Marquardt nonlinear estimation is executed to estimate the motion precisely, the output of our algorithm is motion parameters (attitude and localization) of lunar rover, finally we testified its validity by simulation.