Iterative overlap-part estimation method for generating reliable 3D terrain maps

For efficient wide-area exploration by an autonomous planetary rover, the generation of a global environmental map is very important. A global map is generated by aligning overlapping terrain features from digital elevation maps that are obtained during a rover traveling in a region. Each set of data contains information in different areas, and the overlapping part in each set of data may be missing data because of difference in a position and an orientation of a rover. Conventional alignment techniques based on comparing features assume that datas were measured from very similar positions and orientations. Otherwise, the differences in the measured region deteriorate the quality of a resulting global map. This problem should be addressed by a fairly simple way because of the limited processing capabilities of planetary exploration rovers. Hence, we propose a method for generating highly accurate global maps by considering differences in measured regions and iteratively estimating the overlapping parts in terrain data and we try describe a theoretical proof of our method. The method is evaluated using simulated data and some experimental data obtained from experiments using our mobile robot and experimental rover in a real environment.