Terrain mapping near the vehicle, SLAM and global map building for lunar rover

No Thumbnail Available
Journal Title
Journal ISSN
Volume Title
Sähkötekniikan korkeakoulu | Master's thesis
Space Robotics and Automation
Degree programme
SST - Space Science and Technology
There has been increasing interest to go back to the moon in the recent past because of various scientific and socio-economic reasons. In order to go back to the moon there is a need to study the lunar environment. Although having a permanent mission outpost on the moon is the final goal, it is better to send mobile rovers to the surface of the moon first to study lunar environment before starting the human missions to moon again. With the increasing autonomous mobility of the lunar rovers some aspects become increasingly important namely localization, navigation and mapping. Although the two-dimensional localization and mapping algorithms are becoming more and more mature for indoor mobile robotics, they cannot be used, as is, for autonomous lunar rovers. The terrain on the Moon is not even and would have various kinds of obstacles for the rovers to manoeuvre and traverse. Moreover, environmental features like walls and corners are not available in the environment in which the rovers would have to navigate. In such environments it becomes important for the rover to have the ability to map its surrounding in three dimensions. Although LIDAR based systems have not been widely used on actual lunar missions for mapping yet, they have the advantage of being more accurate and long-range. The focus of this thesis would be to develop and equip a lunar rover prototype with the three-dimensional terrain mapping ability using Light Detection and Ranging(LIDAR) sensor which would help the rover to traverse its environment without collisions. A three-dimensional point cloud was used to map the environment using the Iterative Closest Point(ICP) algorithm.
Halme, Aarne
Thesis advisor
Terho, Sami
Lunar-rover, Terrain mapping, SLAM, LIDAR, Point-cloud registration, Iterative Closest Point(ICP)
Other note