6D SLAM (Simultaneous Localization and Mapping) or 6D Concurrent
Localization and Mapping of mobile robots considers six
dimensions for the robot pose, namely, the
,
and
coordinates and the roll, yaw and pitch angles. Robot motion and
localization on natural surfaces, e.g., driving with a mobile
robot outdoor, must regard these degrees of freedom. This paper
presents a robotic mapping method based on locally consistent 3D
laser range scans. Scan matching, combined with a heuristic for
closed loop detection and a global relaxation method, results in a
highly precise mapping system for outdoor environments. The
mobile robot Kurt3D was used to acquire data of the Schloss
Birlinghoven campus. The resulting 3D map is compared with ground
truth, given by an aerial photograph.